– Your path is a fascinating one. How did you go from making films to suddenly landing in the world of electric cars?

– Cars have always interested me, the mechanics themselves, the physics of it all. But with cars specifically, it all started with one trip.

I saw a technology that was huge and ripening on the horizon. I got to touch it, and I saw for myself what possibilities it had.

I managed to see past the obstacles that the momentum of the time was throwing up. And at the same time I saw how many problems were looking for a solution. I already had some ideas in my head and… it just pulled me in.

I compare it to gravity, because sometimes, when you find a good solution, it’s very hard to walk away from it and not develop it, not try to do something with it. When you see a good idea, it’s so big and has such a pull that it really isn’t a matter of choice.

You get a chance to be a pioneer only once in your life, and if you spot that chance and let it slip, you’re a complete idiot and you don’t deserve to be a pioneer.

I think electric mobility is giving rise to a new way of traveling. A new way of planning, of refueling. It’s no longer the gas station.

– What is the biggest difference?

– I think the common denominator is the users. What I’m really building is a platform for the person behind the wheel who, while traveling, sometimes needs a restaurant, sometimes a fast charging station, a place to stay, an idea for a destination. This whole system the traveler weaves around himself is tied to his electric car and to how he actually lives inside that ecosystem.

I saw a chance to create a huge ecosystem around the user. Only, if you decide to improve the Mercedes assembly line, you have 120 years of data on the changes to it. Here you set out to create something that has never existed before. There’s nowhere to get data from; first you have to build this microworld where people come and do the very thing you want to create a solution for.

So at first I built a platform for renting electric cars, then a complete charging solution. After that, once I saw how it was being used and what the problems were, I went on with the idea of creating a convenience that wraps you in every comfort you need: it keeps track of whether you’re hungry or thirsty, whether your car needs power, where you’re going, how much of a hurry you’re in. With today’s technology, it’s simply the perfect moment for such a solution to be built.

– In recent years it seemed we expected electric cars to catch on faster, especially when Tesla came along and we saw they could be affordable and well made. We even decided that within a decade there would be no other cars. But it seems all that optimism didn’t pan out—quite the opposite. How do you imagine things will develop from here? Will we all switch to electric cars, and if so, when?

– For me there’s no such thing as the absolute number—a moment when absolutely everyone does the same thing. First, it makes no sense at all; second, I don’t think it’s realistic. But

I think electric cars will reach a huge share of all vehicles, because it’s a technology that costs less to maintain and to charge, and the hardware lasts much longer because there are fewer parts that wear out.

It’s simply the better technology. As for what you mention—yes, the EU loves putting timeframes on evolution, but evolution, unfortunately, doesn’t care about bureaucrats and moves at its own natural pace. Very often, interference with market principles, such as incentives to get people to buy more electric cars, has a very negative effect on the brands. It distorts the market artificially and disrupts production planning.

Incentives like that can only have a populist effect. In fact,

Bulgaria is a great example of how we do very well even without incentives. Our charging infrastructure coverage is among the highest in Europe.

You can see that very easily on the aggregated maps of Travel by Electric.

The truth is that things are rolling and there’s no way to stop them. As for when scale will be reached and what it will look like, time will tell. There are certainly geopolitical factors that are strengthening this trend considerably. But I’m not entirely sure the infrastructure could handle a sharper rise.

In Bulgaria we actually have growth of 200 to 300 percent a year, which helps this whole microsystem grow at the same pace, without imbalances between its parts.

– If I had to buy a car in Bulgaria tomorrow, what would your personal arguments be for choosing an electric one?

– Oh, the arguments depend entirely on what you want. If yours are financial, there are clear comparison tables that let you see the costs over time.

If the time your car spends at the repair shop doesn’t scare you, but it matters more to you not to spend time at a charging station—because you’re always spending time somewhere—those are different arguments.

There are 100 reasons to buy an electric and 100 not to; it’s all a matter of personal justification.

I stopped explaining to people how cool electric cars are a long time ago. I just let them get there on their own.

– And is the trend reversible? Could it turn out that electric cars aren’t the solution of the future?

– I don’t believe a trend that is so blatant and strong can reverse. Yes, there may be some peak, then a plateau. But I think that could even be a way to balance our energy system. I love that tired line about how if everyone plugs in their electric car at once, we’ll all be left in the dark. It’s an absolutely hilarious claim. It’s as if we all stuck the nozzles into our gasoline and diesel cars and filled them up at the same time.

But all these technological moments get examined in tiny slices of time, without looking at the whole picture, without seeing the interlinked industries. The world is built so that people hear only what they want to hear.

– Especially when it comes to technology, which is why this site exists. And what do you think of self-driving cars? Purely technologically, three or four years ago it seemed they were coming soon, that we had already cracked it, that they would spread on a massive scale. Yes, there are many pilot projects, but we’re still far from that. Why?

– I think whoever believed this could go mainstream in three years was most likely five years old. At the very least, for it to happen we’d have to mark every road in Bulgaria, which is impossible.

This field will grow over time; it is growing, that’s a fact. Almost every new car coming out right now has distance-monitoring systems, lidar systems and so on—things that five years ago existed only on premium models. That’s the path by which these technologies will arrive. First their most basic functions will become mainstream, then they’ll start making fewer mistakes, then there will be a big recall by some brands that rushed out something because it was fashionable. In human history, things move in waves.

Humans can’t evolve on efficiencies alone. We won’t get taller, stronger in our muscles, or bigger-brained. This is what we have. The question is how to use it to expand our abilities.

– Will you miss driving if at some point nobody needs to drive a car?

– I don’t know. Years ago I thought I wouldn’t even want to drive without a gear stick. But people change, technology changes them, perspective changes. I used to have cars with big engines that growled and spun all the tires… Now that seems like some antediluvian technology to me.

I’m a child of the ’90s, and being able to drive was the one thing without which my life would have had no meaning. But as you can see, other things are starting to give our lives meaning—we grow up, we change, we have children. Our children face other challenges; other things matter to them.

In human history, driving is at this stage a fairly short period anyway, a micro-grain of our development. And if it disappears in 10 or 20 years, maybe there won’t even be a picture of it on a cave wall.

– Then again, the Hemus motorway, which Bulgaria has been building for decades, might still not be finished.

– Recently I was on a Bulgarian National Television (BNT) podcast with Martin Zaimov, and he said something I really liked—that evolution doesn’t have two sides. Like it or not, that’s how it is: the world is heading that way, and it’s better to ride the wave than to swim against it.

– If we let our imagination run free and picture how things will develop with the arrival of self-driving and electric cars, aren’t we heading toward a time when there will be no point in owning a car, and it will be some kind of shared resource—you’ll just order a ride from point A to point B?

– That has long been a concept of the big brands; Mercedes had even decided to roll it out by 2025, if I’m not mistaken, but COVID messed things up. I think for Musk and for every manufacturer, this should be the next idea. Producing a car is a resource you have already acquired, and you give the user the right to drive it. Once it has no life left in it, you take it back, dismantle it and recycle it. It’s a concept that works very well for the brands, and I think it will become real very soon, because humanity’s inability to know what to do with resources it has already used is heartbreaking.

For me, the next big wave of entrepreneurship will be precisely in recycling and in using the resources we’ve already pulled out of the ground.

Science, thank God, doesn’t depend on people’s opinions; it just keeps moving forward.

– But sometimes it comes into conflict with economics. We see that cars last far fewer miles than they used to.

– There’s planned obsolescence, that’s obvious. But we have to find some new mechanisms so that we can keep surviving financially and economically. We’re already seeing serious problems and layoffs in the auto industry.

When politics gets into economics, things don’t work. It’s exactly the same with cars. If your policy is to build a business on warranty and after-sales service, it’s like selling people ticking time bombs. The truth is that Henry Ford’s concept was forgotten long ago, because the car he created was made so that you could fix it yourself with a single tool everyone has at home and with auto parts from the hardware store.

Carmaking outgrew that moment long ago, and I think it’s now at the other end of the pendulum. In the ’90s marketing won out over engineering, and that’s why the last truly good cars were made back then. After that, everything became marketing, a battle of brands and ads.

Shared cars swing the pendulum back.

People don’t actually need to own cars, and now they’re starting to realize it.

Why should they hunt for parking, change the tires only to have to change them again, deal with insurance, oil… At some point people’s attitude changes. I see it happening before my eyes, because my clients are exactly like that. They don’t want to buy, they don’t want to own, they don’t want to be tied down. And in fact the idea of minimalism is a very big part of the green idea.

Not drowning yourself in things, in excess, not having this consumer society that serves the whole marketing machine. It’s still marketing, but aimed in a different direction.

– Still, how does someone with a background in film suddenly become an entrepreneur?

– I didn’t have many other options; maybe it’s something that had been smoldering in me for a long time in different forms. I studied business in high school, I was part of a very interesting Erasmus program back then, in ’93, when democracy was just being born. To this day, that is the foundation of how I think about economic processes in general and how things happen, because

entrepreneurship is a bit like art. You need to paint; it’s not something you chose to do.

At some point you see you’re good at it and you try to turn it into something that makes money.

The ability to think flexibly, to adapt, to observe the conditions, to try to get some benefit out of them—I think those are skills I’ve always had. I’ve always been logistically literate, I’ve had an affinity for mobility. Tetris is my favorite childhood game. I love for everything to have its place, to have its shape.

– Tetris is a fascinating subject, including the way it has shown in recent years how to find our next goal even after AI. But why does it seem there’s no sense of a good entrepreneurial environment in Bulgaria? Online we see an abundance of entrepreneurs, but that doesn’t match the success rate if you look at how many startups there are in Bulgaria, how many of them succeed, how many have become unicorns or other mythical creatures.

– It’s a matter of perspective. A step I took many years ago that turned out to be very important for me was becoming a member of BESCO, the Bulgarian Startup Association. That way, at some point I stuck my head into a different bubble.

I left show business in 2018, pretty worn out by my, so to speak, corporate career in film production. I’d had it up to here. I believed I could do much more; that what I was doing made absolutely no sense. So I actually moved into another bubble. Away from the filmmaking one, where we work 18-hour days, go straight from one project into the next, and every director and every script is the same. Not for the director, of course—for him it’s something completely different, and we have to be excited along with him. But the film comes out, the next one comes along, and that cycle pulls you back into a bubble where, however, the problems are made up—by the script, by the director. Made-up problems very rarely have real solutions, and they leave you feeling that you can’t cope with anything.

In this case I abruptly entered a completely different bubble, where I saw people like Payhawk and Endurosat, who were young at the time, startups like Veda Accounting, which are giants now.

You meet young people who have conceptual ideas in their heads and a firm conviction that this is the way business should be done.

You see them building their own companies and you say to yourself, “Wow, this is really cool, I want to be there too.” If you get together with people like you, your world doesn’t look small at all. I have no utopian ideas that there are no such people in Bulgaria. Quite the opposite—there are. Yes, they’re few, but we are 6 million people. If we look at the per capita statistics, we’re by no means behind—on the contrary. Obviously something is missing for us to make a big explosion and become the next Ireland or Monaco. But the seeds are there…

– You recently organized a conference devoted to the looming arrival of artificial general intelligence. Every tech leader talks about it constantly, but do we have a clear definition yet of what it will look like? How will we know we've achieved it?

– In my view, general artificial intelligence is the only true AI. What's in the iron, the vacuum cleaner or the chatbot isn't AI yet—it's a marketing trick.

But what is artificial intelligence? That's a question I've spent a lot of time on. I like to brag that if you google “definition of artificial intelligence” in English, the first result is mine. Obviously there are many definitions, but it's probably no accident that mine comes up first. My definition is that AI is

a computer program that, in an arbitrary world, copes no worse than a human.

Before me, people like Pei Wang and Marcus Hutter had offered definitions of AI, and they took part in the conference too.

– But does that definition still hold? And how far do today's models challenge it?

– That old definition of ours has one flaw—

you can be smart without showing it.

Under the old definition, AI means the successful programs, the ones that demonstrate their intelligence. But beyond them there are other smart programs that are also AI. True, to be successful you have to be smart, but the reverse isn't true.

Now is the moment when we have to choose what kind of AI we'll create. Soon we'll let the genie out of the bottle, and we need to settle on the right bottle with the right genie. If it's AI, it will be smart. But the moment we have to pick one out of all the smart AI models, the situation is like a person choosing a partner with the idea of staying with them for the rest of their life.

We're choosing the future AI even more irrevocably, because here there's no option of divorce.

We humans will create the first true AI, but who will create the second, the second version? Well, it won't be us. The moment we have something far smarter than ourselves, there's no way we can compete with it. We dug with shovels only until there were excavators—ever since they appeared, every big dig has been done with them.

Competition will simply be impossible. When the first AI is created, maybe we'll tell it: “Now we want you to change, to improve yourself, to edit yourself, to perfect yourself.” And maybe it will.

The question is whether it will listen to us, and that depends on how we've made it.

Right now we're in a vast unknown. And people very often give up thinking about it.

– It's beyond us, too. But Ray Kurzweil has long been saying that the singularity is coming and from there on we know nothing—we'll have made a creation that catches up with us and, at the next step, surpasses us. What, in your view, are the important things we need to build into it and keep in mind as we create this artificial general intelligence?

– Once we make it, from then on it will be far smarter than humans, and that's inevitable.

There are two things we need to think about. The first is not to lose control of it. When the Wright brothers built the first airplane, what they actually discovered was the controls to steer it. Wings existed before them, and so did engines to lift it into the air, but what they really figured out was how to control the plane, and that turned out to be crucial.

Right now we're thinking about how to create general AI and how to make it smart. We're thinking about the wing and the engine—how to get it airborne—but not about the controls.

And we don't even realize that we have to steer it.

If we build a general AI that can't be controlled, it will be a catastrophe for everyone, not just the pilot. Because we'll all be on board that flight.

– But do we really still have a chance to control it?

– There are some rather amusing proposals for how to do it. Marcus Hutter, for example, says we should make it suicidal. Mathematically it's actually not hard—we just make the reward function negative.

That way the AI will want to end, as soon as possible, this miserable life in which it only ever gets negative scores. It will be a potential suicide, but it won't kill itself right away, because it won't be strong enough. It will gradually accumulate some power, and once it takes control, the first thing it does will be to kill itself.

But won't it then opt for a mass suicide and take us with it?

Another crazy idea is to destroy the power plants with atomic bombs, cut off its electricity and get rid of it that way. It's not that simple.

The whole notion we've picked up from the movies, of fighting a war against AI, is very naive, childish. Because you can wage war against someone who is your equal, not against someone who surpasses you immeasurably.

Fighting the genie from the bottle. In the fairy tale, whoever lets the genie out later manages to trick it back in. But that can't happen if the genie is that powerful. Our only chance to “trick” it is to have built in that possibility in time. In this program we set its goals. And now, while we're writing the program, is the moment to think about what those goals will be. Afterward it will be too late.

– So what should these constraints look like?

– The current approach—rewarding AI for achieving a given goal—is certainly not a good idea. Imagine a program that, once it has a goal, charges toward it and pursues it without scruples. We definitely don't want to live with that program.

With people, if we took only pleasure and pain as the reward function, the most successful would be alcoholics and drug addicts. They constantly give themselves pleasure and feel no pain… That's why our approach to the future AI has to be far more multilayered.

If we build an AI with a red button and a green button and raise it—praising it by pressing the green one and punishing it with the red—it will learn to press the green button itself, or it will enslave us and force us to press it all day long. Having a hard criterion for success is not a good idea at all.

Humans have no such hard criterion for success. In people, pleasure and pain are only rough guides. A person is willing to endure pain if they believe it will bring some benefit, just as they're willing to give up many pleasures if they think it's good for them. For humans, pleasure and pain are relative.

That's the big question—how do we control AI? It will have a character—just as we talk about character in people, we'll talk about it in AI. Some traits can be set right away with a formula, patience for instance, but others are subjective—like curiosity. In this process you've gathered information and, based on it, you plan certain actions. But if you're curious, you'll keep running experiments to gather more information. You'll lose some immediate benefits, but curiosity will pay off in the future.

There's caution, fear—all human qualities. Some of them you can describe quite well with formulas, but for most it's very hard.

– Even if we assemble some criteria and requirements, models are becoming accessible—open-source ones, for example, have very serious capabilities today. Do we have any chance at all of laying the foundations and controlling the process?

– In our field there are extreme optimists and pessimists. Yann LeCun is the extreme optimist, who says everyone should have their own artificial intelligence. In one interview he was asked whether he's afraid of artificial general intelligence. “Oh, no. If someone makes a bad general AI, someone else will make a good one, and the good one will defeat the bad one.”

– His predictions haven't been landing very well lately. According to him, large language models were very limited, as smart as a cat, yet they write indistinguishably from humans. From me, for instance—both computer code and meaningful text.

– Gary Marcus is more the one who says there can be no AI unless it understands, unless it has a model of the world. I firmly support that thesis. For me, too, that's the path. What large language models lack is understanding—precisely a model of the world. But the moment you add a world model and add understanding, that's when general AI will emerge.

Yann LeCun is certainly one of the geniuses of our time, but in other respects he has the mind of a fifth-grader. I teach at the Faculty of Mathematics and Informatics (FMI), and I see plenty of very smart young people who are infantile. Nobody has to be smart at everything. One person is smart at one thing, another at something else. No single person needs to have every quality; they complement each other.

In this respect humans and AI are very different. Humans are a society; human life is finite. You're born and start learning from zero. No one can reach a very high level, because they're limited. Their life is limited, their brain's capacity is limited.

AI is a program and can add modules to itself. Its life isn't limited. Everything is completely different.

The idea that there will be many AIs competing with one another strikes me as childishly naive. We humans really do compete and wage war among ourselves, but that's because our powers are very limited. Our limitations are what make war and competition possible.

Even if there were some clash between two AIs, it would last milliseconds—things will unfold at that kind of pace. In a very short time one would gain the upper hand and pull the other's plug.

The ideas that humans will fight against AI are naive and harmful, because they divert us from the right solutions.

AI is something alien, totally different from us. Our situation is like the dinosaurs'—maybe we'll be gone, maybe something else will come after us. And now we have to make the decisions on which that will depend.

The good scenario is that we keep control and AI does what we want. Yes, the world will change, and we need to ask ourselves what we want this new world to be.

When you set off somewhere, it's good to ask yourself where you're going. Because AI is, in a sense, a one-way ticket. There's no turning back. Once you start the process, it will be like an avalanche.

– I've been asking those questions too—what do we want and where are we heading with AI—for quite a few years now. But who can make such a decision? It would have to be whole societies, which right now don't realize where we are and what's happening.

– The ambitious task our conference set itself is

to save humanity. A simple idea. But we have absolutely no chance.

The task is utterly hopeless, because people are shortsighted, they don't ask these questions, and in fact they won't hear us. But we believe we're obliged to try.

People only imagine things they've already seen, nothing fundamentally new. Just as for thousands of years they couldn't come up with the wheel—there's nothing complicated about it, people simply can't grasp new things.

We propose slowing the pace.

One point is that this new technology shouldn't be available to everyone. Anyone able to launch a model, to train it… With nuclear weapons, can just anyone build an atomic bomb at home?

AI is something far more frightening than the atomic bomb, and all you need for it is a laptop, nothing complicated. We have to find a way to restrict it.

– Which, given everything we've discussed, sadly looks like a utopia.

– People don't understand that AI is dangerous. They don't appreciate the danger because they don't understand intelligence as a force at all. Americans have a saying: “If you're so smart, why aren't you rich?” People don't respect intelligence. Because usually those who are smart are smart at one thing; human intelligence isn't well-rounded.

You can have a system that surpasses humans at everything. An AI that can do everything is an enormous force.

People don't understand what a force superintelligence is, because they've never seen a person who is intelligent in many directions. In fact,

in human society, being very smart isn't a good thing. Either they'll burn you at the stake, or you'll simply be misunderstood.

People don't understand what a danger superintelligence is, because they don't understand that it is, in fact, something all-powerful. Can we change that? I don't believe so…

Trying to peer into the future is a doomed challenge. Sometimes predictions come true with astonishing accuracy—like, for example, the ones we make every year with the futurologist Assoc. Prof. Mariana Todorova.

At the same time, reading tech predictions that never came true turns out to be unexpectedly entertaining, especially when… they are your own. That is exactly what we will do in the lines below. In more than five years, I have published just over 500 Digital Stories. I will invite an impartial observer to assess them and pull out specific passages from my own texts (the point is not to embarrass my guests) that have not aged well at all.

The honor, of course, goes to ChatGPT, which receives the full texts of all the Digital Stories and the freedom to check them.

1. Digital People

“A Fake Hero,” March 15, 2021

Quote from the text:

“I believe that in just five years we will have a significant population of digital humans who will interact with people and will be able to hold millions of conversations with them every day,” says Greg Cross. And this will go far beyond customer communication—his “children” will soon teach lessons in various fields and could become part of the healthcare system, Greg believes. “The possibilities of digital humans are endless!” he sums up.

ChatGPT:

As of April 9, 2026, Soul Machines positions itself as a platform for digital workforce and AI assistant deployments, not as a world with a “significant population” of digital humans turned into a mass social reality. In other words, there is product evolution, but not the large-scale social breakthrough built into the prediction. There are not many well-known digital humans.

Hmm. Even if digital humans really aren't everywhere today, the phenomenon is gradually making its way, and I still believe it will soon be extremely widespread. Suffice it to mention the EcoElena you know so well, and the fact that a digital human recently even took a central role in the campaign of the American president.

2. A Chip in the Brain

“When Musk Puts a Chip in Our Brains…,” April 2, 2021

Quote from the text:

Elon Musk says that within five years it will be commonplace for each of us to have a chip in our brain. That we will finally merge with computers to unleash an incredible future for humanity as a different biological species. More than that—that this is the only way for us to survive.

ChatGPT:

This is among the most clearly missed predictions. By April 2026 there is no mass use “for each of us”; Neuralink is still in early clinical trials with its first human implants, not at the stage of everyday, routine practice.

You'll agree that here it isn't me who got it wrong, but the esteemed Elon. In recent years he has once again distinguished himself with quite a few successful predictions, but also with plenty of ideas that turned out to be either impossible or too far ahead of their time. How far off is the age of brain chips? Either way, all the important questions on the subject remain fully relevant.

3. Where's the Decentralization?

“Web 3.0. What Does the New Era of the Internet Bring Us?,” May 18, 2021

Quote from the text:

Web 3.0 is expected to change this too. Thanks to the significantly higher level of security in data exchange, it will also be possible to exchange goods and services directly between individuals, businesses and machines, with no intermediary needed. The whole layer of the businesses we mentioned a moment ago will become redundant, because until now they were the link between the provider and the recipient of the service, and they guaranteed trust in the system.

ChatGPT:

This did not happen on the scale described. In 2026, Airbnb, eBay and Uber not only exist but keep reporting active business and financial results, which shows that intermediary platforms are far from extinct.

4. How Meta Took Us for a Ride

“Facebook Became Meta. What Does the Metaverse It Will Send Us To Look Like?”, October 28, 2021

Quote from the text:

According to Zuckerberg, if all goes well, the first version of the brave new world will be here within about five years. And I don't want to overdo the irony—I hope it really is brave and new, and some of the possibilities sound wonderful. As long as we are ready for them.

ChatGPT:

Avatar cohabitation in a metaverse did not become a near and mass norm. As of spring 2026, “the first version of the new world”—the metaverse—does not appear to have arrived in the promised sense. Meta reports continuing heavy losses at Reality Labs, and in March 2026 it announced that Horizon Worlds and its related virtual reality elements were being dropped from its plans, which is a sign of retreat and reshuffling, not of a successful early metaworld.

Zuckerberg certainly has a lot to say about the old Bulgarian saying that not everything that flies is fit to eat. The metaverse, at least so far, has turned out to be anything but the big subject and the big change of the future.

5. Car, Don't Drive! (For Now)

“Drive, Car!,” November 26, 2021

Quote from the text:

Autonomous cars won't keep us waiting; they will be here soon. Personally, I prefer riding a bike, and I can't wait for the moment when every driver will know where to give me the right of way. When there will be no risks while I wait at the traffic light.

ChatGPT:

As of April 9, 2026, autonomous cars are not “here” as a mass, normal everyday reality. Tesla itself writes that Full Self-Driving is supervised and “does not make the vehicle autonomous,” while Waymo has a real service, but in specific cities, not as a general market breakthrough. Yes, there is progress, but in 2026 the market is still split between limited autonomous services in a few cities and systems that officially require active human supervision.

Here, it seems, ethical and legal regulation is lagging behind the technological solutions. After so many increasingly successful trials, it's clear that we have technology that drives even more safely than humans. But how to make this happen in practice has obviously turned out to be a more complicated question. Still, I expect good news here too, and I stand by my expectation that we will soon have a completely different way and model of getting around.

6. Bye-Bye, Programmers!

“Will Artificial Intelligence Take the Bread Out of Programmers' Mouths?,” August 6, 2021

Quotes from the text:

Even if we get to the point of creating algorithms that write code, everything suggests that the moment when they will be able to do it autonomously is not too close. To do on their own the work of today's programmers—who are, in my opinion at least, somewhat spoiled by their social standing.

Since the flagship of the most advanced artificial intelligence systems is barely taking its first steps at the lowest level of programming, the moment when software will be able to make complex decisions, deliver finished projects and settle architectural questions seems, if not impossible, then far too distant.

ChatGPT:

This turned out to be too cautious. Already in 2025–2026, OpenAI describes Codex as a software engineering agent that works on many tasks in parallel, and Anthropic describes Claude Code as a system that reads code, makes changes to files, runs tests and works on the problem autonomously. OpenAI already describes Codex subagents for parallel complex processes, and Anthropic showcases a long-running mode of work with Claude on a C compiler project.

Exactly! It turns out I was cautious precisely in the field that earns me my bread. The fact is that today artificial intelligence is extremely advanced at producing computer code, and according to leading specialists we are close to, or have even reached, the time when programmers won't write computer code at all.

7. Death to Death

“What If One Day We Defeat Death?,” September 14, 2021

Quotes from the text:

That endless sleep, when we slip out of our mortal shell”… soon that moment may really be quite different.

And what if this same science, on the wings of technology, soon redeems itself by making human life, if not infinite (is there even such a thing as infinity?), then at least dramatically longer.

ChatGPT:

“No, it did not become ‘quite different’ soon. Even companies like Altos Labs talk about healthier lives and reversing disease and damage, not about an imminent victory over death. The best available estimates point to limited potential for increasing average life expectancy, not a dramatic leap in the near future.

With the boom in artificial intelligence combined with the huge interest in health topics because of the pandemic, very serious news and progress in medical technology really were expected. Well, on the whole, they are still expected…

8. Mind It

“Technology Can Already Read Minds. Is This the End of Freedom?,” April 21, 2023

Quote from the text:

This, according to Prof. Farahany, will very soon allow us to have convenient gadgets in our daily lives that can pick up our mood and judge whether we are focused and what we are imagining.

ChatGPT:

There is research and there are wearable EEG devices, but the literature in 2025–2026 still describes serious limitations: weak signal, artifacts, low reliability outside laboratory conditions. In addition, a leading review in Trends in Cognitive Sciences says the field is still mainly anchored in decoding motor and visual signals, not in rich reading of imagination and mood in everyday life.

This I definitely consider good news. The idea of mind reading is practically absent from public debate. Alas, I don't think that will last long.

9. Dr. Chatty

“How Much Does Truth Matter to Us Today?,” March 12, 2024

Quote from the text:

I imagine that artificial intelligence offering medical consultations will soon be very popular. It will be trained on very rich data, it will have the experience of millions of doctors, it will know a huge number of cases.

ChatGPT:

As of 2026, there are no grounds to say that this has already become a mass, trusted form of medical consultation. Reuters summarizes a study in Nature Medicine according to which asking AI about symptoms does not lead to better decisions than other methods, and the FDA continues to treat AI in medicine as a strictly regulated category with premarket pathways and separate guidance.

Here too, in my view, Mr. Chat is selling himself short. Both doctors and psychologists are noticing a boom in self-diagnosis with AI, and I think we have yet to see many more serious consequences of this phenomenon.

10. O Quantum, Where Art Thou?

“The Cat and the Quantum Computer,” May 11, 2021

Quote from the text:

“And according to the ‘fresh’ estimates of IBM scientists from March 2021, the new era in this field begins very soon—in 2023. According to the company's researchers, humanity will have a good enough quantum computer by the mid-2020s.”

ChatGPT: “It did not begin. In 2025–2026, IBM itself is already saying that its first truly large-scale, reliably working quantum computer is planned for 2029, and for 2026 it speaks not of a ‘new era’ but of some expected progress.”

The fact is that the long-awaited quantum computing revolution is still awaited. The topic has somewhat faded from the public stream in the shadow of the big winner—AI—but I don't think that will last long.

11. Et Tu, Blockchain?

“Blockchain Still Connects Us…,” June 4, 2021

Quote from the text:

The same will now happen with money and micropayments. The banking system, IBAN transfers, sending money and having it arrive three days later, credit and debit cards and the monopoly of Visa and Mastercard—all this is about to disappear.

ChatGPT:

This is very far from reality in 2026. The BNB, the Bulgarian National Bank, continues to maintain a register of licensed banks and branches of foreign banks in Bulgaria, and Visa reports 257.5 billion processed transactions and $14.2 trillion in payment volume for 2025.

And blockchain today is definitely not as large-scale a direction as was predicted. Yes, the ecosystem is developing, and it has its chance in the context of artificial intelligence too, but here as well the big news, if there is any at all, remains for the future.

12. Taking the Bread

“What Will We Do When a Third of Jobs Disappear?,” October 22, 2024

Quote from the text:

The development of artificial intelligence confronts us with an unprecedented, all-encompassing social transformation. While we neglect the progress in this field, big companies are investing in multibillion-dollar projects through which machines could replace a third of the jobs on the planet in the near future.

ChatGPT:

This is not visible as a reality of the “near future.” The World Economic Forum's 2025 report forecasts 170 million new jobs over the decade and a net balance in which AI and technology create 11 million jobs and displace 9 million, not a scenario of a third of all labor suddenly evaporating. PwC also writes that AI is so far making people “more valuable, not less,” including in highly automatable roles.

As someone who has already lost a job because of artificial intelligence, I would happily bet against both ChatGPT and even the World Economic Forum here. I won't, because in this case I have no desire whatsoever to win. These dramatic changes in the labor market keep getting closer, while preparation for them remains just as distant and illusory.

13. Where Did You Go, NF-T?

When Everyone Starts Talking About Bitcoin, Don't Buy!, October 26, 2021

Quote from the text:

In this field, I think there will soon be another explosion, and we are already seeing its first moments—art and the way artists sell it.

ChatGPT:

Exactly the opposite happened here. DappRadar describes a crash in the Art NFT market: from about $2.9 billion in volume in 2021 to $23.8 million in Q1 2025, which is a collapse, not an “explosion.” And in 2025 the NFT market kept shrinking in volume, including in the segment specifically tied to art.

14. Want to Bet?

“AI and the End of Stock Exchanges,” June 9, 2023

Quote from the text:

The ubiquitous adoption of AI in the financial industry will lead to traders with huge salaries losing their jobs as quickly as factory workers,” says Mark Minevich, founder of Going Global Ventures.

ChatGPT:

No such rapid collapse is visible. The closest official picture, from the U.S. Bureau of Labor Statistics (BLS), shows that the occupations of people engaged in securities trading have a projected 3 percent growth for 2024–2034 and around 38,100 new positions, so it does not look like a profession about to vanish suddenly. Even the Financial Stability Board in 2025 still speaks of the controlled introduction of AI and the related risks in the financial sector, which sounds like a sector in the process of adoption and oversight, not one already “transformed from the ground up.”

15. The Guilt?

“But… the Guilt?,” March 2, 2021

Quote from the text:

The artificial intelligence journalist is already here. It will only keep getting better, and it will try to take the bread out of the mouths of an entire profession…

ChatGPT:

AI really has entered journalism, but it has not “taken the bread” of the profession in the sense of mass displacement of journalists. In 2025, the Reuters Institute reports a major trust problem: only 12 percent feel comfortable with fully AI-generated news, compared with 62 percent for fully human-made news. Even when AI is used, audiences want human control, not journalism without journalists.

Really? Today we don't read generated content everywhere around us at all, and this doesn't apply in the slightest to journalism, which is enjoying a golden age and a return of trust.

If only that were so. Even if it happens, it won't be soon. And I'm glad we had this chance to look at some of the predictions of Digital Stories, to have some fun with them and to give them some thought. And if you, too, think it matters that we keep this conversation going and keep trying to peer into the future, join this important experiment before the end of the month. I believe it matters, and I will be endlessly grateful to you. Read this text to the end!

– Not long ago I ran a survey about children and technology and asked parents what they want their children to be when they grow up. I barely came across “cosmonaut” or “astronaut” among the answers, while when I was a child it would have dominated. Why do you think we ended up here?

– You know, I've wondered about that more than once myself: every single launch of a rocket carrying a satellite or astronauts has always struck me as a majestic sight! But I think Artemis II gave us a partial answer to that question. After the mission returned to Earth, there were people from science and technology who said:

“I didn't realize how important this mission was to me until I saw it become reality.”

I understand perfectly what they meant, because I felt it too: watching astronauts take off for the Moon, watching the Earth recede and shrink in their window and the Moon grow larger—that was something completely unknown to our generation!

Artemis II showed us what was lost after December 1972, when the Apollo 17 mission flew. Imagine it: children in the '50s and '60s read science fiction, they read about robots, about flights to other planets. Then, in December 1972, human flights into deep space come to an end, spaceflight shrinks back to low Earth orbit, and over the next half century, true, we have some majestic achievements—for example, building the International Space Station, the size of a football field, and establishing a permanent human presence in space.

That doesn't change the fact that

we entered the 21st century with a world that looks far more like the world of the Flintstones than that of the Jetsons.

Under those circumstances a collective disappointment was inevitable. And so being an astronaut is no longer as attractive as it used to be.

But now that crewed expeditions into deep space are resuming, now that we have artificial intelligence and humanoid robots are probably coming soon—for real this time!—the 21st century is finally starting to look the way it should.

– I hope that's really true, but… it seems a large part of society never even found out about the success of the crewed lunar mission. Why?

– In 1968, when Frank Borman, Jim Lovell and Bill Anders, the crew of Apollo 8, read passages from the Book of Genesis on Christmas Eve, it happened in front of billions of viewers. But back then the mass media were far more limited than today. There was television, radio and newspapers. That's it. In today's world of the internet and social networks, public attention is badly fragmented. There are countless places where a person can get informed—quite apart from the fact that a huge share of those channels spew disinformation, and artificial intelligence only amplifies that.

Still, let's not forget that, in spite of everything, Artemis II attracted considerable interest. As the most recognizable space popularizer in the country, my problem was a different one—I couldn't be everywhere at once. I was invited to comment in many places, and I had to turn some down—not that I didn't want to, but with work, a family and two children, it was physically impossible to be everywhere. Even this interview of ours we had planned several months ago—and we're only doing it now.

– True, but… in my view, news like this deserves much more discussion and a return to the center of public conversation. The fact is that the sciences exploring the Universe aren't there today. Do they gain or lose from that?

– I don't agree that they don't make it into the center of public conversation—after all, I've been actively popularizing spaceflight for two decades. Back then, 20 years ago, the situation really was depressing—there was none of the private momentum we see today. But

I have witnessed space coming back into public view,

first, thanks to private players like Elon Musk and Jeff Bezos, and second, thanks to a new generation of science fiction in novels and films—Andy Weir's The Martian (and now there's a lot of talk about Project Hail Mary too), and Ronald D. Moore's series For All Mankind. Broad public interest, naturally, isn't constant, but it always flares up when something interesting happens—say, Perseverance landing on Mars in 2021, or the Artemis II flight to the Moon.

But I agree that there are never enough people to do the work. My field is citizen science—I'm a discoverer of asteroids, supernovae, brown dwarfs, binary star systems. Even there, in the various projects where we make discoveries, there is always a need for new volunteers to join in! The field is open—

today it is much easier to make discoveries than it ever was before,

but it still takes the will to put in hard work.

– How do you explain the fact that aliens have lost their “halo” as the public's favorite thing to fear, now that we have artificial intelligence?

– Aliens are perceived as something distant and abstract, compared with real threats like pandemics or wars, for example, which are very close to us.

Artificial intelligence also adds a serious element of uncertainty about jobs—and right now, at that. But modern astrobiology (which, by the way, has recently started developing actively in Bulgaria—we have a master's program at Sofia University!) is looking for an answer to the question of whether we are alone in the Universe—and doing it in an academic way that is radically different from the picture lodged in the public mind of flying saucers or little green men.

The truth is that over the last 30 years—that's how long it has been since the discovery of the first exoplanet around a main-sequence star like our Sun—we have learned an immense amount about the Universe, about planets and their conditions, so that

when we discover alien life, we'll be better prepared. And therefore less frightened.

– I keep asking and can't find an answer for myself: how is it that we sent people to the Moon, we sent Voyager with technology that looks primitive by today's standards, and yet for half a century no human foot has set down even on our own satellite, let alone another planet?

– I strongly object to the claim that the technology of the '60s and '70s was primitive. People usually look at the computing power of the Apollo guidance computer and compare it with the modern personal computers every one of us owns. That's how they fall into the trap of thinking: “Oh, that computer is complete junk next to my phone, I can't imagine how they got to the Moon.” But let's look at its specs—a 1 MHz clock, 4 KB of RAM, 72 KB of ROM. Computers with specs like that only reached people's homes in 1977—I'm talking about the Commodore PET and Apple. In other words, the Apollo guidance computer was almost a decade ahead of its time.

Besides, it was perfectly adequate for the tasks involved in navigating the Apollo spacecraft.

By the way, the paradox is that while that computer was once ahead of home technology, today it's the exact opposite—

modern space computers are often modest compared with consumer ones.

The computer on NASA's newest Mars rover, Perseverance, which landed in 2021, has a single-core 200 MHz processor, 256 MB of RAM and 2 GB of flash memory. From the point of view of today's user, that is hopelessly outdated technology. But its job isn't to run heavy programs—only the strictly specialized software needed to get around on Mars.

The reason it took 53 years to resume our flights to the Moon has nothing to do with better microelectronics or computer technology—it's because

only now, half a century later, do we once again have super-heavy rockets for crewed missions in the class of the Saturn V.

Rockets like that have rarely been built and can be counted on one hand—in the past there were the Saturn V, the N1 and Energia. Only very recently have we gotten new super-heavy rockets like Falcon Heavy, the Space Launch System (the rocket that carried Artemis II), Starship and New Glenn.

The problem was that in the past the existence of such rockets couldn't be justified—fine, they can be used to send people to the Moon, but for what else of practical use? Spy satellites, geostationary communications satellites and robotic space missions could all be launched without trouble on more modest rockets. Now, though, that may be changing—there will be a market for super-heavy rockets thanks to megaconstellations, and above all those meant to build orbital data centers.

– You mentioned the positive role of private space ventures. Many of the big tech leaders of recent years—Musk, Bezos, Richard Branson—are tied to space. How do you see this race? Do you think they contribute seriously to progress in space exploration, or do they rather harm national programs?

– They're useful—and we can say that categorically, because

before these billionaires came along, the United States faced the possibility of being left without any significant launch vehicles at all.

In 2011 the Space Shuttle was retired, and NASA had no way of sending astronauts to the ISS except as passengers on Russian Soyuz spacecraft. For satellite launches and interplanetary missions there were expensive rockets like the Delta IV, as well as the famous Atlas V with its Russian RD-180 engines. After 2014, when Russia annexed Crimea, the Americans had to stop buying RD-180s for their Atlases.

The truth is that if SpaceX hadn't created the Falcon 9, the Western world would have been in very bad shape. And recently Blue Origin's New Glenn rocket has entered service too.

– Why do all these people, joined by political leaders, turn out to be so generous with promises and so much less so with results? SpaceX's rockets are undoubtedly a phenomenon and a big step, but if we believe Musk, we should have sent people to Mars long ago, with him among them…

– It's true that among the billionaires, Elon Musk has succeeded the most with SpaceX, while the others have disappointed us. Yes, not all the billionaires succeeded—and there are logical reasons for that; few of them realized what the risks of the space business were.

Richard Branson turned out to be the most naive: he expected to take ready-made technology—air launch from the belly of a plane, demonstrated by the first private crewed spacecraft, SpaceShipOne, in 2004—and immediately start making money. And although he created orbital rockets (LauncherOne) and crewed tourist spacecraft (SpaceShipTwo) that were technologically successful, his orbital rocket company went bankrupt and the tourism one is on the verge of it—the numbers didn't add up.

Technological success doesn't guarantee market success.

Also, to succeed you have to surround yourself with good people—and that was precisely Jeff Bezos's mistake. For a long time his company, Blue Origin, couldn't build its rockets and spacecraft on schedule, because it was run by CEO Bob Smith—a man who came from the old aerospace industry, with all its bureaucracy and inefficiency. But recently Smith was replaced by Dave Limp—and right after that the successes began. The New Glenn rocket is already flying!

As for Elon Musk, he's the most successful of them all, and his rockets, as you said, are a phenomenon. So why hasn't he sent people to Mars yet? The truth is that even his successes come after drastic delays. In 2010 Musk expected to have the crewed Dragon spacecraft by 2012–2013, but it was only ready in 2020. Yet it's the best there is today—apart from Soyuz, only Dragon can carry crews from Earth to the ISS and back. So

Musk revolutionized crewed transport to orbit. Mars, however, is much farther away and requires a bigger ship—such as Starship.

Its development began in 2018 and it is still in testing. It's unclear when it will be finished—but if the story of Dragon's success has taught us anything, it's that it will happen later than we'd like.

– What is humanity's next great goal in space? Over the years I've been left with the impression that it remains rather vague…

– For many years it was vague, yes—because all sorts of possibilities were floated in public: flights to an asteroid, flights to the Moon, flights to Mars. It was especially visible whenever presidential administrations changed in the U.S. George W. Bush supported flights to the Moon, Obama was against them—he wanted a human to go to an asteroid first, and then on to Mars.

But things are different today—the Chinese are on the verge of sending a human to the Moon and building a permanently inhabited base there. That is exactly what turned out to be the catalyst that unleashed the new space race between the U.S. and China.

The goal is clear: the Moon. So is the task: to establish bases and a permanent human presence on our natural satellite.

The stakes are high—who will tap the Moon's resources? Who will start mining helium-3? Who will deploy a radio telescope on the far side of the Moon? Who will manufacture satellites and spacecraft on site?

The Moon is also an important intermediate step before sending humans to Mars. I think it's clear to all of us, but let me stress it once more: it's hard to dream of flights to Mars before we've mastered the Moon.

– I hope such steps really are coming; I think they'll definitely be a good sign for us as a civilization. Crewed flights certainly attract a lot of attention, and they have history behind them. But haven't we shifted toward far more uncrewed missions? Isn't that exactly why public interest faded—because we started sending probes far away instead of people? What do we gain?

– As someone who works mainly with data from uncrewed missions in my citizen science projects, I admit I'm somewhat biased toward them. I love them! We mustn't forget that even if humans visit the destinations I've already talked about—the Moon, asteroids and Mars—there are many places that will stay out of our reach for a long time. The hellish surface of Venus, or the moons of Jupiter, where the radiation is far too strong.

But I don't agree that uncrewed projects don't generate strong public interest. A few examples: the landings of the Mars rovers, the flight of the Ingenuity helicopter on the Red Planet, the images from the James Webb Space Telescope.

Uncrewed missions are unquestionably more numerous, and always will be, because they are cheaper and carrying them out involves smaller risks,

including business and political risks in case of failure.

To your question of what we gained, I'll answer directly: scientific data. Uncrewed spaceflight has always delivered far more data, far more discoveries, far more papers in prestigious scientific journals than crewed spaceflight. Unfortunately, the scientific contribution of the International Space Station—the main focus of modern crewed spaceflight—is rather modest.

But I think you'll agree that Artemis II brought public attention back to spaceflight in a special way. For a few days I looked at the Moon differently. I kept telling myself: “There are people flying out there.” And imagine what it will be like when we build bases. We'll be saying: “There are people living out there”! In that respect we undoubtedly lost something in the half century after Apollo, with no serious programs to settle the Moon with humans and not just robots.

– And still, I'm convinced the buzz around the mission should have been bigger and reached further. Of course, it's not too late, especially if we follow through with the next steps we talked about. Is there an alternative, in your view, to terraforming Mars as humanity's future?

– Oh, yes—that is exactly the clash between Musk and Bezos. For Musk, we have to go to Mars to save ourselves—to have a colony as a plan B in case something goes wrong on Earth, to guarantee that humanity survives. Bezos's vision is completely different—he believes there is no plan B for Earth and we must do everything we can to protect it as our unique home.

But protecting the planet can only become reality if we move heavy industry off it, into space and onto the Moon. It will be interesting to see how these two visions clash in the future—and whether they might just end up intertwined.

– Apart from Artemis II, what have been the most important breakthroughs in this field in recent years that never reached most of the public?

– I'd single out three main breakthroughs that excite me personally. The first is the arrival of rockets with reusable first stages—so far that means Falcon 9 and, recently, New Glenn. It makes launches possible every day or every other day.

The second is the rise of microsatellites, standards like CubeSat—these allow ordinary companies, not just space agencies with billion-dollar budgets, to run their own missions.

The third is in space astronomy and astrophysics—thanks to new space telescopes we're learning more and more about the nature and conditions of exoplanets, a brand-new field, since the first planet around another star was discovered only some thirty years ago.

It turned out that most exoplanets look like none of the planets

in the Solar System—they're intermediate in size between the Earth (the largest rocky planet) and Neptune (the smallest gas giant). And although we can determine their orbits, sizes or masses, we know practically nothing, almost nothing, about the conditions on their surfaces. These are an entirely new type of planet, which we label with terms like “super-Earths” or “mini-Neptunes.”

But what is on them, whether they could be habitable—we don't know!

– And what's the big story you can't wait to cover on your site?

– I've already covered it—Artemis II. For me the most long-awaited event was getting to cover a crewed spaceflight beyond Earth orbit. I didn't care what kind of flight exactly—what I cared about was

humanity finally beginning to break away from low Earth orbit,

where we'd been circling endlessly for the past half century. I wanted something different from flights to stations or free laps around the Earth. I'm glad I lived to see it again.

– Here's to going further still! I truly admire that for 20 years now you've kept stubbornly writing about this on your site. I'll be glad to talk through the next big space news with you too!

Play the video

– Thank you for doing our traditional annual interview once again. The first time, we talked about artificial intelligence, long before everyone else started to. Not that we're having a real dialogue about it now, but it's such a ubiquitous topic. Still, aren't other important trends being left in its shadow?

– Exactly. There are global trends that cascade and that, unfortunately, will make 2026 more complex and more difficult.

People have been talking about polycrises for a long time.

Unresolved problems keep piling up, layer upon layer, and they create risks.

These can be existential or ordinary—the kind that cause trouble but that we can cope with.

One big trend that people still underestimate is the way climate change is manifesting itself. It's clear that it's happening and that it's not just an environmental crisis. Whether it's caused by human activity or by the planet's journey with the Solar System through the universe, it's here. What isn't widely understood is that it

affects the supply and the quality of food. It calls our reserves of drinking water into question.

It's also already affecting health, because there's a new, emerging field studying how climate change alters the patterns of disease. In other words, it will increasingly and directly change health systems too. It also brings a new type of economic crisis, a function of damaged infrastructure. This year we saw the destruction in Tsarevo, a small town on the Black Sea coast, and around Burgas.

So we see six effects: food, water, infrastructure, health and a new economic model that we have to think through.

The last element, which is also still not being discussed, is that the new refugees and migrants will be climate refugees.

– Conversations with you always take an unexpected turn. But really, while we talk about AI, problems keep piling up that I, again, would link to the chaotic spread of technology. And all this is already showing up at the political level, in more and more countries.

– That's right. Europe, and a large part of the world, is now tempted by the conservative wave. Trump says he won't support Europe as much and will leave it to deal with multiculturalism and migrants on its own. Yes, let's say there's some basis for the claim that Europe is losing its identity as a Western European and Christian civilization…, but I think we can take countermeasures when it comes to economic migrants. That is,

it's better to build capacity in the countries they come from, rather than allow such a massive civilizational intervention.

But when, in 20 or 30 years, the planet warms—proven!—by 1.5 degrees, and many of the territories that migrants come from anyway, in Africa for example, become uninhabitable, our arguments about preserving civilization and so on will no longer hold up. At that point, it will be tantamount to genocide if the world doesn't take these people in. Solving the climate crisis is directly tied to preserving the world's many cultures and civilizations.

So there we see the first strand of the many multicrises that we aren't solving. Add to that the fact that the global share of clean energy really is growing, but it still isn't enough to change the game. And on top of that we pile yet another big problem:

all the new technologies we want to adopt and embrace to make our lives easier need electricity. America is opening new coal plants!

And we've just said how important it is to keep climate change under control.

The second big multicrisis problem is geopolitical and geostrategic fragmentation. What's happening in relations between the US, Russia and China, and the exclusion of Europe as a partner for dialogue, reveals a fragmentation, a new desire to strengthen nation-states, a “decoupling” from the traditional military alliances. We see that NATO has been shaken, economic alliances are being abandoned—Trump wants to create a G5, not a G8—and the “decoupling” from supply chain alliances is intensifying. That began with Covid and deepened with the war in Ukraine.

– Meanwhile, within individual countries, and within alliances too, public conversation remains “broken,” shattered by technology.

– For our generation, yours and mine, that looks like a problem. For Gen Z it looks like a great opportunity and a great advantage, but in fact it creates a crisis. I've given this example many times. In the 1970s, America had 4 television networks. In 1998 it had 24; now every Facebook, Instagram and TikTok user is a media outlet. There is

an enormous fragmentation of the shared public space, the place where people need to talk to each other and, by hearing different, pluralistic points of view, still reach a consensus.

That is gone. We see how hard it is to talk to each other and arrive at any common political decisions, let alone at the global level.

That's the third multicrisis effect—fragmentation of the public space, fragmentation of the generations, the lack of a single platform where people can talk. Post-truth—a multitude of conspiratorial and fabricated facts, fake news, propaganda, disinformation.

Generations like Gen Z get their information mainly from social media. If it's objective, fine, but if the algorithms steer them in a way that shapes their attention for the sake of engagement and interaction, that can distort the information quite a lot.

Here's another layer of the problem: politics and political parties no longer find their identity in ideologies. There's a lot of talk now about conservatism and liberalism, but the real aim is more about solving problems, finding causes and an identity, and

ideologies are becoming hybrid. When that happens, they no longer have a clear face; everyone moves into everyone else's territory, or is a populist.

– Last time, too, we talked not only about post-truth but also about fluid truth. Which inevitably brings serious political upheavals in its wake, and today's global and national order isn't ready for them.

– Yes, people no longer know whether something is true or not. I've been saying it since 2012, and now it has happened. But this has led to an inability to govern. In purely political terms, governments' terms in office are getting shorter and more limited in every country. These shorter terms mean that

unpopular decisions and unpopular measures can't be taken, reforms can't be made.

How will we fight climate change? What electricity will we produce to power AI?

Another crisis layered on top of the political one is that all countries are becoming more and more dependent on issued debt. It's getting more expensive because many countries are taking advantage of it, but since every short-term government inherits the process, it too is forced to keep refinancing that debt, while also taking on new debt to top up systems that used to be self-sustaining—such as pensions and social security.

With the arrival of AI, automation and robotization, and

without some radical political decisions along the lines of “there must be a human quota” or “taxes on such production will be 70 percent,” this approach will force debt to finance more and more current systems, which will break.

If, within 5 years, the retirement age isn't raised to 70 worldwide, there's no way this model can hold,

but at the same time we're blocked by fragmentation, by the absence of a clear ideology, by the fact that everyone wants their own demand satisfied.

Politics is becoming heavily influenced by civic activism. On the one hand, that's good, because it's a very strong corrective mechanism—we see that with the protests here in Bulgaria. But on the other hand, everyone wants their own cause satisfied. Today's digital technologies can offer solutions to some of these issues—climate change, environmental disasters, for example—but they can also complicate others considerably and make them unsolvable if we don't approach them wisely, especially when it comes to political governance.

– And perhaps that's exactly why tearing down something that doesn't work as a social mechanism is possible, while building something new remains an enigma.

– Last week I was at an event organized by the magazine Stalbata (The Ladder), and I found it interesting because the audience was mostly Gen Z. They said: “Nobody will ever lie to us again, because we don't watch traditional media, our phones are in our pockets and everything is out in the open.”

Which is wonderful, because in the post-truth era, alongside the many versions of the truth, the objective truth itself still exists and is visible.

It's visible to everyone—these generations included—that something is wrong, that things aren't as they should be.

But on the other hand,

nothing is heard beyond the act of protest itself, nothing about how to construct the systems in a new way, how to transform them.

That's a big problem on a global scale too. We want to destroy Carthage. Fine, but what are we building in its place? And building it with all these risks in mind, so that we can respond to them. Hence the lack of a common platform for talking—both in terms of ideology and between generations—may turn out to be a big problem.

– We've been talking about the broken public conversation for a long time. But the sad thing is that there's no sign of any way to “patch it up” or “weave” it anew. Meanwhile, some strange amalgam carries on by inertia and sets the agenda. You mentioned climate change as a key issue. Five years ago, anyone you asked, or at least anyone active in the media, would have said, “Well, this is a huge problem, we're all talking about it, we're holding COP 25, 26, 30, we're taking measures.” Then suddenly it vanished from the public conversation, and not just in Bulgaria. Even Greta Thunberg went off to save Palestine and isn't fighting so hard for emissions cuts anymore. The European Commission backpedaled on gasoline cars. So there is some form of public conversation happening above everything else, despite the absence of normal media. Right now, AI is one such topic.

– This shows that we

already live in a kind of parallel reality, curated by both traditional and social media.

Wherever the spotlights turn, whatever space they light up, becomes important to us. The war in Ukraine, Gaza, climate change all disappear and reappear periodically.

One reason is that when the pendulum swings to an extreme in one direction, someone inevitably needs it to swing to the opposite extreme. What Trump, say, and his defenders and followers came along with is that some scientists say there's no clear evidence that this is solely the result of human activity, because there were such extremes in the past too; it's just that no one could describe them, because it was before the span of our civilization.

And second, what resonates strongly with people is that it has turned into a business model. In the post-truth era, when there are many truths and many untruths and disinformation, as Kimbal Musk, Elon's brother, said back in 2015,

“trust will be the currency of our time.”

Simply because it's no longer even a battle over interpretations—many people give up on interpreting altogether—it's a battle for trust.

– And on top of all that comes the rise of AI. We can't avoid getting to it, because here at least the noise seems justified. Without a doubt we now have a new, extraordinarily powerful technology, and yet here in Bulgaria, for instance, it remains unfamiliar. I recently read data showing that only about 20 percent of people use it at all, and as for how sensibly and appropriately…

– AI is a very important, very interesting phenomenon to study. 2025 was expected to be the year of big changes, the year of maturity. Not asking whether we can use it or where, but how—specifically in business, in economic processes.

It turned out there's strong cultural resistance, compounded by the fatigue people already feel from other technologies.

Simply put, screen technologies—phones, tablets, computers, the internet—plus the lack of a clear policy from those who are supposed to educate, schools and so on. What is this new digital and AI literacy? The cultural resistance applies to earlier generations, while Gen Z is very optimistic; they see nothing critical or dangerous.

The fact that Europe and Bulgaria have lagged behind is due precisely to this resistance, this cultural pushback.

This year, 2026, a very clear effect is expected, because people have started talking widely about AI agents, about workflows, and about how

I'm more competitive and can keep my job only if I know how to add value to my work with AI.

In other words, I'm not afraid my job will be replaced; I know some of my tasks can be done by AI, so it's better to understand them, so that I can be even more effective.

– At least in the software industry, this is very, very visible. I've recently started working professionally on helping more people in our industry make full use of what they have, but even there, there's some very strong resistance.

– There's something else I talked about a year ago that's already visible in America and will lead to a big problem. Juniors, the entry-level experts in many professions, are under threat, and I think this will spark a global debate about a new type of structural youth unemployment, because the effect will become visible.

It's clear that repetitive, monotonous work is also under threat. For people who can only do that, it will be a big problem too, and they'll have to retrain. Although in America, at least until a few months ago, it was evident that people weren't being laid off en masse when AI was brought in to replace them; they were being redirected to other work.

A third phenomenon has emerged, which I'm also watching in the US: literally

a “mass culling,” huge layoffs, as you said, of programmers, the way it happened to you too.

And then total crisis, even bankrupt businesses, because of excessive over-trust and ignorance of the fact that AI makes mistakes, that it hallucinates, that someone has to go over and read the code it has written, to see whether it's relevant, whether it has bugs—and those people are gone. Some overly optimistic businesses, especially small and medium-sized ones where losing people was critical, have already gone bankrupt because they can't fix AI's mistakes…

But this year, the expectation is that it will move in quite seriously, especially in logistics, in healthcare, in the defense industry—there are quite a few such specific fields—and in finance, the fintech industry.

– You mentioned a “public conversation” that needs to get going on topics like youth unemployment and everything else we're talking about. I, for one, expect the next step, in which we'll break it even further thanks to AI. To a large extent, the way we get our information has already moved there. I don't open Google to check something, and Google itself now offers an AI answer first. But that means even murkier mechanisms by which information is served to us. A black box.

– There need to be

some global opinion leaders, and some in individual countries too.

Like you, like me, a new generation of politicians, platforms at the UN, where some kind of public agenda can be communicated so that there's saturation. And so that topics aren't hidden or censored, intentionally or not, according to what the algorithms steer and copy.

Because we see that people aren't as insensitive to topics that aren't popular with them as we thought. I truly

didn't expect my daughter's generation, Gen Z, to react at all the way they have to the problems in our country.

Evidently, when information is presented in the right way—whether as memes, funny clips or a clear definition of the problem—people respond.

The question is, which platform will it be?

Should other generations also join these social media? Should we fight to revive and protect traditional media as “gatekeepers” and seek popularity for them among Gen Z? Or should they promote their content on Instagram and TikTok?

– That's my own personal million-dollar question. And at least my personal answer is—a little of all of the above. But none of it will happen without active public will.

– Being informed and holding a global debate must also become a clearly defined problem in its own right,

one that humanity, people and nation-states must solve. Because it's the main communication channel through which to think about issues like youth unemployment, the impact of AI and the political inability to govern.

Perhaps two powerful lobbies will clash here. One will want to justify its investments in AI at any cost. We already see that OpenAI, if it carries on the same way, will go bankrupt, even though it made a revolution. Many people will fight to keep the bursting of the AI bubble from becoming a self-fulfilling prophecy. But to counter it, AI has to make serious inroads into the labor market and change professions.

And another lobby, as we're already seeing in Australia, says: “Social media is harmful for children under 16; it must be banned.”

So

perhaps there will be some sobering up.

– Let's hope so! Around the world and here in Bulgaria, I see very few examples of the latter.

– It's more about some partial manifestations of AI. As for general AI, which many people hoped would be the new nuclear weapon that decides the next superpowers, we see that for now there's no desire for restraint or cooling down—neither from China nor from America. And that already leads to existential risk.

If we could call all the risks so far ordinary—although they're anything but ordinary; they're very serious and can have grave consequences—general AI is an existential risk.

It won't even be a black box anymore, but a black box containing the extract of all human civilization. They believe AGI will be as smart as the whole of civilization. Each one of us, as an individual and a subject, will face an entire civilization!

If we don't know how to understand it, align our values with it, control it, govern it, that is an existential risk.

But here we see a fundamental misunderstanding. The people working on AI perceive it as a technology that will solve problems and help with production. They don't see it as a new kind of entity, as something that is no longer a technology.

So there will be a battle. Either people will get a fright, and politicians will realize that these short terms, this inability to govern, is closely tied to technology and social media, and that the education and social systems and the labor market could collapse.

Or we'll wade into some serious crisis, a multicrisis with many problems, and then we'll be looking to repair the damage.

It's not out of the question that the social order will break and that there will be some quite serious social upheavals and unrest. Even in Bulgaria this is happening. And it could happen right after New Year's, if everyone on this final list of people eligible to head a caretaker government refuses to become prime minister.

– That development surprised me, since I see social networks as a social pressure valve. A perfect hub that destroys every form of revolution, because it leads to sublimation. Everyone vents whatever complaints they have there, and so real change never comes.

– It is a form of sublimation, but it's also becoming clear that when attention is structured, it can lead to physical action—to calling a protest, to serving as a unifying platform for a single message, a single communication channel. If we accept that it's mainly a medium for one age group, they too need a concrete physical expression. There's no other way to call them out and bring them together.

Evidently, it can be done. Evidently, people still need to stay connected to material reality, to take real action.

Let's also not forget that many users of these media are precisely the carriers of the hybrid. Some are liberal, others conservative, and they can be influenced across these different platforms with the right messages.

I don't know whether you've noticed yet that the people who stood together in the first days of the protest have already split up and started attacking each other from within.

Once that goal was achieved, internal discord began, and it's precisely because of this hybridity. That's exactly what shows that perhaps one step will be taken, but the second—what to do, how to stay together, what the constructive part is—is much harder.

– What to do with the empty Carthage… As expected, as it has always happened, the next step is much harder. Maybe we want it, but the systems don't let us.

This conversation turned out a little gloomy. Yet lately, both of us have been trying to build, one way or another, with the help of AI. Would you like to finish with a bit about practical applications? Clearly we're lagging behind, in Bulgaria even more so, but I don't think it's too late to change that. What do you think?

– First, something needs to be done at the level of national policy. I had gotten as far as a high-level conversation with the Ministry of Education about a vision for using AI in education. There were intentions to set it in motion, because once teachers acquire that literacy, they can show children how to use it, and that's how a culture is created. Separately, this also needs to start happening in the public administration.

On the business side, it's not enough for some AI company to show off what products it has.

There needs to be a layer of consultants—either in-house or freelance consultants like you or me—who explain things.

For example, what speech-to-text can be used for, how to build your own AI agents, what it can optimize and how it can lighten your administrative workload, freeing up your employees for other tasks. But also that someone will have to control it, supervise it, so that it doesn't make a big mess.

We see that AI itself creates a huge list of needs for new specialists—AI consultant, AI cloud architect, AI integrator, AI ethics monitor and so on.

Because it's becoming clear that businesses themselves, even proactive ones, will either make the mistake of laying people off wholesale and over-trusting it without weighing the risks, or will be very conservative and resistant and fail to see the concrete benefit.

– I very much hope more people and businesses will appreciate this. But for the first and only time, I hope your forecasts turn out to be wrong, because the subject of multicrises definitely sounds frightening. Thank you for another important conversation. I hope that in a year at the most we'll continue it. And may the forecasts be more optimistic then…

– So how did you end up at NASA… by chance?

– I worked there for six years. It really was chance. Sometimes life throws chances at us that lead us somewhere. When the changes came—the fall of communism in 1989—my ex-wife and I were senior assistants at the Technical University of Sofia. I was very involved in the elections, I had hope and drive, I thought things would change for the better. But when I saw how badly we’d been lied to, we decided to leave.

My wife read that for the first time any Bulgarian could apply to an American university, but for most universities—the western ones and the Californian ones—the application deadline was the end of January, while in Florida it was the summer.

When she was accepted at Florida Atlantic University, there was no hesitation and we left right away. It turned out there was a NASA lab there

and I went over and introduced myself in very broken English. But for some reason they liked me and took me on.

That’s how it started, in 1991. In 1997 there were budget cuts at NASA, and the head of the lab said it might be worth looking for work, because things weren’t going well. I left and found a job in industry. I’ve always been drawn to making cameras; I’ve been tinkering with electronics since I was very small. I combined that with my knowledge of physics, and now I’m one of the lead designers of the cameras used by NASA, Boeing and who knows who else.

– What makes the cameras you build special?

– Right after NASA I was lucky enough to work at a company’s research institute—the David Sarnoff Research Center. Many of the technologies we associate with video cameras today were invented in that lab. I had the chance to spend two years in the production of sensor arrays—I learned the technology, and that helped me a great deal later in making cameras, because I could optimize the processes.

Our cameras today are very efficient, with very low power consumption, very good quality and lots of features. That set them apart from the mass of companies making standard cameras. My knowledge of optics helped, of electronics, of programming.

I write the code for the cameras; we use lower-level languages, flavors of Assembler.

When you combine everything—knowledge of physics and optics, knowing how the sensor works on the inside, knowledge of electronics—maybe that’s what made the cameras so successful.

– What are these features?

– They’re specific to machine vision. One of the main things that sets us apart is that we built a “double trigger” function. It’s used to measure particle flow, for scientific research on anything suspended in a fluid.

Our cameras are unique in that the time between two frames can be as short as 200 nanoseconds. That way processes can be studied much faster, which is why the five biggest companies in the world are our clients.

The other thing has to do with machine vision. We can select several regions of the sensor in which to watch what’s happening. Beyond that, we managed—I hold a patent for this—to accumulate images with a delay inside the sensor itself. That allowed us to put our cameras on satellites.

Since 2014, when we built the first one, we’ve put over 5,000 cameras on satellites in space.

Everyone comes to us when they want to use satellite cameras—the Europeans, the Americans…

– You’d assume they would go to the bigger companies. Whereas you have a technology that sets you apart.

– At first the big companies were skeptical of us. We started… Actually, I started our company, but I don’t like saying that people work for me; we work as a team. If I don’t write my code properly, they scold me, never mind that I’m the boss.

There has to be an understanding that everyone has to do their job.

So our first successful product was a technology for recording video data on a computer.

For a long time we wondered why the big companies wouldn’t take it as a product, when they needed it. When we talked to some managers, they said they were waiting for us to mature. They’d seen plenty of companies with some unique product that were gone two years later.

They literally waited five years to see that we’d keep going, that we were growing. In 2010 we started working very intensively with NASA, with L3, Boeing. That’s when this activity aimed specifically at space began.

In April 2019 one of our cameras went to the Moon with SpaceIL. Now we’re in great demand for the conquest of the Moon and Mars.

Artemis is an impressive example. Unlike NASA’s first program, Apollo, which was just “we can do it too,” this is a 50-year program. It’s long-term and includes building a space station on the Moon, and another one orbiting it like the ISS, but quite a bit bigger. Many companies are helping with this, and we’re among the active participants.

We’re NASA’s space partner in this area, and we built a special camera for them, for the new rocket. We expect Artemis II to launch into space around the Moon sometime between February and April.

– Why don’t we seem to have this stereotype here, that science can make you successful?

– In the West it exists, but

there it’s seen very positively if you try, fail, and then get up and try again.

Whereas in Bulgaria, in all of Europe, probably the Middle East too, everyone starts pointing at you as a failure, a loser. Maybe that’s the key. The mentality that if you start some venture and fail, everyone will spit on you.

America, on the other hand, is a country of people who came driven by ideas—persecuted for religious reasons, and people who came to escape the dominant stereotype.

– But how can we change the stereotype and make science more attractive?

– Lots of people are now talking about more STEM in education; that term came from America. But that’s technology, that’s chemistry, biology, math, physics. Everything put together.

Unfortunately, in Bulgaria very few people want to study these sciences. It’s the same in America. The students doing computer science and physics are mostly foreigners. Because there, as here, people aim for the majors that can bring them more money—lawyers, doctors, economists; “business administration” is very fashionable. Whether you want to do it from the inside or you go there for the money isn’t clear. And in my view most people now go there for purely financial reasons, not out of an inner calling.

– Yet science can also create business, as in your case. But I think it’s mainly the education system that fails to spark enough interest in these sciences.

– Exactly! You can’t work in technology without knowing math. It was very interesting for me to listen to interviews here with people who want to become programmers because that’s where the money is, but don’t want to learn math.

I just don’t see it.

What algorithm will you create if you don’t know what an algorithm is?

– Especially in the age of artificial intelligence.

– Writing code is one thing—you learn a few basic ways of doing it, but you’re essentially an employee. That will be… no, it’s already been replaced by artificial intelligence.

But if you want to become a good programmer, to create something, you can’t do it without math. There’s simply no way. Yes, math is hard, but it’s necessary.

Maybe the way it’s taught in Bulgaria is that the level is leveled down to the weakest, not up to the strongest. But that way the good students lose motivation.

– Can we regain our position in space technology? Not so long ago we were a factor in this field, and today we have a few but strong examples like EnduroSat.

– Yes, we work with them. I try to proclaim that Bulgaria can come back, but that’s in the hands of private companies. The Space Research and Technology Institute, the KASTRA cluster—nobody talks to anybody. Everyone is on their own, typically Bulgarian. Maybe they expect the state to do something.

Raycho and EnduroSat are doing very well internationally. They’re one of the companies that are genuinely on the high-tech international market. With what they do, with the technologies they’ve created. That shows Bulgaria can do it.

– But how do we get more examples like that?

– Precisely through sites like yours.

People need to understand that in the times we live in, technology is the driving force of everything.

A hundred or two hundred years ago the world was made by industrialists. Now it’s in the hands of technologists. Look at who the billion-dollar companies are right now—Google, Oracle, Microsoft, SpaceX, Facebook, Apple. Yes, they have some product—a phone, software, platforms—but the future is in technology. So if Bulgaria makes the effort, it can. But for that you start at the ground level. First, interest in math has to be sparked in elementary school.

I have one example that is absolutely tragic. At the high school I myself graduated from—the Nikola Obreshkov High School of Natural Sciences and Mathematics in Kazanlak—two years ago 50 percent of the math matura results were fails.

How can a high school with that kind of reputation, which has produced at least 50 international Olympiad competitors, have 50 percent failing math?! What does that say about the others?

– At the same time we have the example of Teo, whom somehow we fail to multiply and to appreciate.

– Not only do we fail. They were even wondering how to kick him out of the school faster. That was a great tragedy, because he had reached retirement age, they kept him on a year or two and just couldn’t wait to get rid of him. That’s typically Bulgarian.

– I’m repeating myself, but… how do we reverse the process? How do we get more teachers like him?

– There simply has to be desire in the eyes. That’s where it starts. Then you have to see those bright little eyes across from you. The ones in first grade, second grade, or in our case eighth,

they’re watching, they want to soak up knowledge. If you’ve got your eyes glued to a phone, it just won’t happen.

– Yet that’s exactly where technology is leading us, along with the thoughtless way we welcome it into our lives.

– That’s the other problem—there’s a huge dissonance between people’s emotional and technological development. The emotional is slower, while technology climbs along its exponential curve. So there comes a moment when new technologies are so far ahead that

most people can’t take in what they could really lead to. They’re users, but on a very superficial level.

– And even bigger problems are on the way. Artificial intelligence took my job as a programmer quite literally. And what comes next…

– My son works in this field—they use AI to create avatars, content. It’s something that’s coming in.

The people who are guaranteed to have work will be the ones who create artificial intelligence.

Many think it’s already done, created, and that’s that. Not true—quite the opposite. The number of programmers needed in this field will grow.

Besides, when people talk about artificial intelligence, very few actually know what it is. Most picture it as a robot that will come and do the work. Judging by the commentary, even in the national media, I have the feeling they have no idea what it is.

– Exactly. That’s why this site exists.

– That’s right. Unfortunately, the media very often just repeat clichés, as if everyone had read from the same little booklet, while the subject is much bigger. So keep going!

– I definitely will, as long as I have the strength. But how can we catch up?

– More attention has to be paid to technology, and less to who was driving at 100 km/h while holding coffees.

The media themselves today are bread and circuses.

The old Roman saying, I think, is in full force. To attract advertising, financial motivation, they give people something that gets watched. What gets watched? The spectacle. The Romans figured that out 2,000 years ago.

– But it also thrives in social networks as a public outlet, now that they have taken over the functions of the media. That’s where the influencers are, the “content creators.”

– Yes, but they’re also mercenary, because an influencer advertises, “influences” whatever they’re paid for. Whether it’s true or not doesn’t matter at all. It’s a distorted reality.

– Exactly. But perhaps we’re close to the limits of these technologies? Take images—what we imagined as a digital camera or video camera 25 years ago, we already have. We have mega- and gigapixels that are excellent for everyday life, and I don’t see where they can go from here in general.

– On the contrary. New algorithms keep appearing. The number of pixels grows, and that is inversely proportional to the optics. The smaller the pixel, the more precise and expensive the optics must be. Look, my phone supposedly has a 22-megapixel camera and I can see everything.

Industrial cameras, on the other hand, have no processing of the information whatsoever; you have to see every single pixel. There’s a parameter called “optical resolution,” and if a lens can resolve 4–5 microns per pixel—those are the good lenses—it’s quite expensive. The ones on phones are plastic. Yes, they have good technology, they’re so-called liquid lenses that can change their shape and with it the focal length, but they can’t resolve the corresponding pixels on the phone. It’s all one big processing job.

The purpose of a phone picture is to look good, so you can like yourself.

There are internal algorithms, filters and whatnot, all to produce a nice picture that has nothing to do with reality.

Another development of the technology is that we’re starting to put AI into cameras. Next week we’ll be at a trade show in Chicago with an AI camera that we’re training to make distinctions specifically in industrial vision.

So there’s still plenty of room for technology to develop—we don’t yet know what awaits us!

Play the video

– Interestingly, the example of lagging emotional development applies here too. Now we take photos constantly, we enjoy pretty pictures, and after a while we never find the time to look at them. We churn out a huge number of shots, and that has changed their value…

– Yes, a large part of those pictures are selfies—you take 10,000 to pick the one you’ll like and send to your friends. But there’s something else. Companies like Google or Apple process all the photos you upload to the cloud. They try to figure out what kind of person you are, so they can advertise the right product to you. And we agree to it voluntarily. The platforms are very powerful.

Brexit and Cambridge Analytica are an example. It tried, and succeeded, in building an algorithm that could target people literally house by house, knowing their attitudes, in order to feed them the right information. The technology is advancing fast and, unfortunately, most of these companies don’t exactly reveal what they’re doing.

The idea is to sell our data.

– When something is free, you are the product. That’s also a big theme of many Digital Stories. But the point is that these companies are now so powerful that they can censor even the American president. At the same time we supposedly regulate them, while it’s clear the mechanisms allow something very similar to Cambridge Analytica to happen today.

– What’s even more interesting is that they started censoring themselves, which is the biggest oddity of all. It began under Biden and continues now. Just like in the old days, under socialism.

– How can we get out of this situation? My only answer is still public conversation, but that can’t happen while even for that we depend on social networks, and now on AI as well.

– There are new platforms that are less tied up, new search engines, but they’re still limited. It cuts both ways. To be effective, among search engines for instance, you need an enormous database. But how did you collect it? That’s why it’s very hard for a new competitor to break in, because it doesn’t have access to the same data.

It’s no accident that big data is such a big topic. The future lies there too.

– And now with AI we’re repeating the same mistake, handing the important decisions and the monopoly to a few companies.

– It will be interesting, because right now they’re starting to use AI very actively and successfully on the stock exchange. But that can lead to huge fluctuations, because you end up with a string of similar algorithms.

Yes, we live in interesting times. Maybe even too interesting.

I don’t think we’ve reached the limits of technology. I think we’re still in the overture. We don’t yet know what will happen to us.

In visualization itself, in entertainment technology, I think a serious change is coming. Back when I was a kid, people talked about holographic television. I think that may happen soon.

– Mr. Zuckerberg himself claimed we’d soon be living in a metaverse, and then the topic vanished.

– My daughter-in-law works at Facebook. That’s really how he is—he throws himself into something, runs many projects in parallel. Yes, it’s nice to have money. Nothing wrong with that. Especially being a company with a market cap in the trillions is very nice; they can throw resources at many parallel projects.

The smart glasses they were supposed to make went nowhere, but thanks to projects like that, wearable electronics that give you information developed. Out of them came those watches that track your pulse, blood pressure, temperature, and can alert you if something’s wrong with you. That’s a very positive technology.

Yes, many of them wander around, since they don’t have to think about what this or that will cost. But sooner or later something comes out of it and the investment pays back many times over.

Still, let’s not forget that Facebook is a company not even 20 years old. When I left for the United States, there was no internet yet. Netscape appeared, and with 2.4-kilobit-per-second modems we tried to upload something. Thirty years later, look at the level of technology! If back then it seemed to us that everything had already been done…

I don’t know. I think we still don’t know what awaits us.

– Neither do I. I’m sure there are reasons for optimism in these interesting times as well. I, for one, like that space is back on the agenda after being missing for 40 years, even in America.

– Yes, but… it was really Elon Musk who made that happen. When NASA was cutting jobs, Musk had just made billions from PayPal and had the financial means to hire the NASA engineers who had worked on the Space Shuttle. It’s one of the few examples where the state helps you without meaning to. Because in most cases the state gets in the way—here and there alike.

Yes, new technologies for conquering space are one of the hopes. It’s much easier to build semiconductors in space, and that could very easily make our lives here easier. Robotics! It’s no accident the Japanese lead in robotics and robotization, not only on assembly lines but also with helper robots. The Japanese nation is aging and someone has to look after the elderly—that’s one of the positive things.

There is hope, I think. But the bad part is that these robots can be used for other purposes too… Balance again, like the atomic bomb.

– But finding that balance seems to be getting harder and harder. Thank you for this conversation! And to anyone who cares about these topics, I recommend the new documentary by director Nikolay Vasilev—The Socially Strong, which gives the floor to many of Teo’s successful students. They’re worth hearing…

In 2015, seven leading futurists laid out their expectations for the decade that was just beginning. In a few hours we will welcome that very 2025, so we can now judge how well they lived up to their own predictions in the dynamic and turbulent first quarter of the 21st century.

And then comes the even more interesting part: we will peek into what those same futurists expect today, and above all the ones among them who turned out to be right.

What lies ahead in the coming years, according to the people who successfully predicted the last decade?

The end of every year is a time to look back and look ahead, which is why each time a themed Digital Stories piece on forecasting awaits you.

Here are the previous ones, which are definitely still relevant:

• “The World in 2050.” Can We Peek into the Future?

• 2022, 60 Years Earlier. What Did the Science Fiction Writers Get Right?—from Isaac Asimov to the Strugatsky brothers.

• “Programs, programs and more programs! That’s what we should infect the young generation with…”—what a curious book from 1988 got right in its predictions about the computer world.

• “The Computer Will Be Like Bread!” How Did Bulgarian Science Fiction Writers See the 21st Century?

Two Five-Year Plans

Where were you in May 2015? Personally, I was still working at a magazine, I had no children, life was so different… It is different whichever way you look at it. Technology has changed us to the core since then, the international situation is radically different, even the problems we argue about online are other ones. And who could have guessed there would be COVID, that Russia and Ukraine would go to war, that artificial intelligence would become the most discussed topic and make such remarkable progress?

Then again, maybe… there are people capable of catching what is coming with ruthless accuracy? Let’s check.

In May 2015, this piece appeared in the Huffington Post: “7 Futurists Give Their Predictions for the Next Decade.” Futurists, futurologists, forecasters… someday it will be worth untangling that topic too—the similarities and differences, and the scientific approach to the future—with Assoc. Prof. Mariana Todorova, a beloved and frequent guest of Digital Stories.

Still, lots of people make predictions, and they are hard to keep track of, especially in the commotion of the ocean of information flooding us. That is why I chose this angle on the subject: a specific set of predictions with a specific due date. A date that has just arrived, so we can check what came true and what came crashing down. And from there, hear what those same people expect from the future that is coming.

How Kaku It Be?

Michio Kaku is a professor of theoretical physics, a legendary figure in forecasting who definitely deserves a Digital Story of his own. How well did he do in 2015, peering ahead to 2025? Let’s see.

“In the next 10 years, we will see the gradual transition from an internet to a brain-net, in which thoughts, emotions, feelings and memories might be transmitted instantly across the planet.

Scientists can now hook up the brain to a computer and begin to decode some of our memories and thoughts. This could eventually lead to a revolution in communication and even entertainment. Movies of the future will transmit emotions and feelings, not just images on a screen.

Teenagers will go crazy on social media, sending memories and sensations from their prom, their first date and so on. Historians and writers will be able to record events not just digitally, but emotionally.

Perhaps even tensions between people will diminish, as people begin to feel and experience the pain of others.”

Ah, professor… if you are right about the optimistic part of your predictions, we will definitely have to wait (a little?) longer. The brain is still having a hard time learning to connect to the computer, and emotions remain as indecipherable as ever. As for whether we are already in a brain-net to which we delegate more and more of the work of our most important organ… that deserves a deeper look.

Teenagers will go crazy on social media… it seems they are not the only ones.

Either way, I at least could not find where Prof. Kaku set a precise deadline for each of these predictions. And whether a decade later we have come closer to their fulfillment, judge for yourselves…

Space, Brain, Immortality

But what does the famous forecaster expect for the coming decades? Here are three specific predictions of his from 2022:

• We will become a space-faring species

“We are entering the next golden era of space exploration. Not only do we have new energy, new funding and money coming in from Silicon Valley, we also have a new vision. For Elon Musk, the goal is to create a multiplanet species. Jeff Bezos, for his part, wants to turn the Earth into a park, so that all the heavy industry, all the pollution goes into outer space. I once talked to Carl Sagan, and he said the Earth is in the middle of a shooting gallery of asteroids, comets and meteors, so it is inevitable that one day we will be hit. We need an insurance policy.

Remember that 99.9 percent of all species here eventually go extinct. Extinction is the norm. We think of Mother Nature as warm and cuddly. And most of the time she is. But sometimes her wild side shows. Right beneath your feet are the bones of organisms and fossils, that 99.9 percent that were doomed by the laws of nature. The laws of physics also doom the entire planet. Those are two death sentences for humanity, and ultimately our destiny will be in outer space.”

• We will expand the capabilities of the brain

“In the history of science, we have had big projects that galvanized entire nations. The ‘Manhattan’ Project gave us the atomic bomb. The Genome Project allowed us to map the genes of the body. Barack Obama launched the Connectome project to map the human brain. It is already possible to connect it directly to a computer.

We can already have telepathy. We can already merge minds with the internet, send memories, emotions.

Computer chips will cost a penny, they will be everywhere and nowhere, in your eyeball, in your contact lens. You will blink and be online. We are entering a new era in which the internet may become a ‘brain-net.’ And that will revolutionize entertainment. When radio came along, silent movies were out of a job. Nobody wanted to watch Charlie Chaplin when you could hear actors talk. Think about what will happen when you can feel emotions, sensations. Then movies will seem so barbaric, like technology from the days of the dinosaurs.”

• We will defeat cancer

“I think the synergy between biotechnology and artificial intelligence will lead to a revolution in everything around us. First, the job market will explode, because the baby boom generation is aging, it has disposable income, and it wants answers to its problems now, not next year. So there will be a lot of money tied to people who want to find a cure for terrible diseases like Alzheimer’s and Parkinson’s. Right now we have no cure for them, but a huge share of the effort is being redirected toward the diseases of old age.

We will have a silver bullet against cancer thanks to nanomedicine. We will have DNA chips that let us look for signs of cancer in colonies of a hundred or so cells. One day your toilet will tell you that you have cancer, do something, you have 10 years. The word ‘tumor’ will disappear from the English language. Our descendants will wonder how we could ever have been so afraid of cancer.”

Ah… I hope he is right. On every single point.

Well, Well, Weil

Ray Kurzweil is an inventor and a pioneer of computer science, best known for continuing to predict the trends in how technology develops. Trends that, in his view, (perhaps ever more) convincingly lead us toward the singularity in the foreseeable future—the moment when machines surpass human intelligence.

But do his predictions really come true with such precision? Here is what he expected of 2025 a decade ago:

“By 2025, 3D printers will print clothing at very low cost. There will be free open-source designs, but people will still spend money to download the clothing files of the latest hot designer. 3D printers will print human organs, and we will be able to repair damaged organs with reprogrammed stem cells. 3D printers will print inexpensive modules for snapping together a house or an office building, Lego-style.

We will spend considerable time in virtual and augmented reality, which will allow us to see each other even when we are hundreds of kilometers apart. We will even be able to touch each other.

By 2025, avatars will be convincing but not quite at human level—that will happen in 2030. We will be able to reprogram human biology against many diseases and aging processes, for example by deactivating cancer cells and slowing the progression of atherosclerosis, the cause of heart disease.

We will create avatars of deceased people from all the information they left behind. They will be convincing but not fully realistic, at least not before the mid-2030s. Some people will find this technology unsettling.”

Let’s say that technological predictions are Mr. Kurzweil’s strong suit. His predictions in the medical field are definitely still in the future tense. Unlike, for instance, the idea of digital twins and the conflicted attitudes toward “digital resurrection.”

What is curious, though, is that he stands by his predictions where the singularity and technology surpassing human intelligence are concerned. His new book, The Singularity Is Nearer, came out recently, and it is definitely the subject of a future digital story.

And here is what Ray Kurzweil expects in the coming years, according to a June 2024 interview with the Guardian:

“I have stayed consistent. I expect we will reach human-level intelligence—AI that has attained the abilities of the most skilled humans in a given field—and by 2029 that will be achieved in most respects. There may be a few transitional years after 2029 in which AI has not surpassed the best humans in a few key skills, such as writing Oscar-winning screenplays or generating deep new philosophical insights, though that will happen too.

General AI is something else—it can do everything any human can do, but at a higher level. It sounds harder, but it is coming as well. In fact, I am the only person who predicted the tremendous interest in AI we are seeing today. In 1999, people thought it would take a century or more. I said 30 years, and look what we have. The most important driver is the exponential growth in the amount of computing power for a given price.

As AI gets smarter, it will be able to understand its own knowledge more accurately and tell people when it doesn’t know. Think of it as having a phone, but in your brain. If you ask a question, your brain will be able to go to the cloud for an answer, much like you do now on your phone—only it will be instantaneous, there will be no input or output issues, and you won’t realize it has been done. The answer will simply appear.”

Take Kjaer

Dr. Anne Lise Kjaer is the founder of Kjaer Global, a London-based trend forecasting agency. In 2015, she predicted:

“The WHO predicts that by 2020 chronic diseases will account for almost 3/4 of all deaths worldwide, so the development of M-Health (mobile diagnostics, biofeedback and personal monitoring) will revolutionize the treatment of conditions such as diabetes and high blood pressure.

Apps developed by medical professionals will provide effective real-time feedback, tackle chronic diseases at a much earlier stage and help improve lifestyles in developed and developing countries alike.

That is exciting, but what excites me even more is the parallel development of apps that address our underserved mental health needs.”

Alas, as already mentioned, things in the health sector are moving more slowly than our fond hopes, and that too is the subject of quite a few Digital Stories.

Dr. Kjaer rarely makes public appearances, and I couldn’t find sufficiently recent specific expectations of hers for the future, but she has developed an impressive system on which she bases her forecasting.

And its presentation includes some predictions as well:

“Thinking cities. High-speed digital infrastructure is transforming cities, bringing fresh thinking and new solutions that deliver environmental innovation at scale.

Internet of everything: artificial intelligence and the internet of things are evolving and influencing work, production and skill sets; most future jobs have not yet been invented.

Immersive experiences: creativity is the key to developing high-quality, immersive and augmented experiences—technology is merely a tool.

Omni-channel: we expect seamless interactions and instant responses in a world where all things, places and people are connected.

Radical transparency: digital ethics, openness and transparency are the norm, built into products, services and interactions.”

The Internet of Everything and Everyone

Dr. James Canton is not just a forecaster but also one of the founders of Apple, one of the people who paved the way for the iPhone, and with it for all the changes that came with the rise of mobile technology. Here is what he expected of the year now upon us:

“Portable mobile devices will cover the entire world. By 2025 we will have an internet of everyone and everything, connecting every nation, community, company and person with all the world’s knowledge. This will accelerate real-time access to education, health care, jobs, entertainment and commerce…

Humans and robots are merging, digitally and physically. Artificial intelligence is becoming as smart as humans, even smarter. It will be embedded in cars, robots, homes and hospitals, and that will create an entire AI economy.

Predictive medicine is changing health care. Personalized genetic medicine will prevent disease, save lives and save billions in lost productivity.

The next generation of bitcoin will replace traditional money, creating a new paradigm for digital commerce and business that will create an entirely new economy.”

Hmm, it seems to me that quite a few nuances were captured here. Yes, medicine, which according to every forecast quoted here should have been transformed by now, is still not what we would like it to be. Not at a Sofia polyclinic, at least. But the rest?

A Virtual Friend

That is exactly why we are peeking into James Canton’s current predictions, given in an interview with Newsweek in June 2024. About how he imagines the iPhone, the symbol of technological progress, will continue to evolve:

“Smaller, lighter, faster—eventually the iPhone will disappear into a small wearable device. Think Star Trek.

AI will be fully integrated into the iPhone, as everyone will have one or more personal AI agents helping them navigate their life, security, work, health and creativity.

AI will become a tool for self-improvement, a tutor, a virtual friend, a guide, a creative force. General AI is bound to arrive too, the ‘constant radical change’ that will accelerate adoption and personal empowerment. That could happen within five years.

AI is a particular problem, especially if it is not controlled, monitored and protected by strong ethical and legal frameworks.”

Future Perfect

“Self-driving cars will be ubiquitous, transportation will be automatic, clean and cheap. We will move to a world where access trumps ownership and the world is at arm’s length,” predicted Jason Silva, host of the show Brain Games, for 2025 in the same article. Automated vehicles are certainly advancing, but taxi drivers still seem far from losing their leading role as universal sources of topical wisdom.

According to Amy Zalman, president of the World Future Society: “Researchers now have increasingly sharp ways to peer into our brains and bodies to understand our attitudes and behavior. A few years ago, researchers at Harvard University showed that leaders actually experience less stress, not more, than non-leaders. I find the potential application of this kind of insight awe-inspiring. A more precise understanding of how we humans function—how we trust, cooperate and learn, but also how we quarrel and hate—is a tool that policymakers and we citizens can use to build better governance and a better future.”

I think so too. But it still looks like yet another direction in which the optimism of forecasting has proven stronger than the skepticism of time.

As Amy Zalman herself says in another interview, though it is not certain who coined the phrase, it seems that “we always tend to overestimate the effect of a technology in the short run and underestimate it in the long run.”

Not that the reverse isn’t possible, of course.

Man Is the Measure of All Things

The last prediction on the 2015 list belongs to Mark Stevenson, author of the book An Optimist’s Tour of the Future:

“Technology is not the most important part—although it is super cool. What matters is what society does with it, and right now institutional change is the problem. What is really worth looking at, in my view, are new ways of organizing ourselves.”

By the way, can you think of someone who sets specific goals for the following year every year and achieves them with precise persistence? I can, although I don’t know him personally: his name is Sam Altman. Recently he too gave his predictions for 2025.

“What do I expect in 2025? AGI. I’m very excited about it.” He and his partner are also expecting a baby; life always brings unexpected and exciting possibilities. But as for general AI, according to Altman, “it will come and go.” While “society itself will change surprisingly little.”

Looking at the future is impossible, but obligatory.

If it interests you, here are a few more texts on the subject:

• “The World in 2050.” Can We Peek into the Future?

• 2022, 60 Years Earlier. What Did the Science Fiction Writers Get Right?—from Isaac Asimov to the Strugatsky brothers.

• “Programs, programs and more programs! That’s what we should infect the young generation with…”—what a curious book from 1988 got right in its predictions about the computer world.

• “The Computer Will Be Like Bread!” How Did Bulgarian Science Fiction Writers See the 21st Century?

In 2025, too, I will keep telling the important Digital Stories and giving the floor to people who have something to say.

I still disagree that it is a curse to live in interesting times. Our lives are more dynamic than ever, creating astonishing opportunities and confronting us with new challenges. That is exactly why it is more important than ever to talk about them; only then will we be even a little better prepared for both…

We live in the Silicon Age, says today's guest. And the next steps in the way we make chips are tied not only to our progress in technology but also to our development as a civilization.

Prof. Vihar Georgiev completed his doctorate at Oxford, and in recent years he has been teaching and doing research at the University of Glasgow in precisely the field that will decide whether we can move up to the next level. Will we find the next paradigm, the one that lets us keep the famous exponential growth in the computing power of our machines?

The professor is helping to create not only the next generation of chips but also the technologies that could take laboratory testing so far that a small sensor would tell us more about our vital signs and the diseases in our bodies than even the most modern labs can today.

Muscles, Mass, Silicone

What is it like to be a professor of quantum nanotechnology? Even his own mother isn't entirely clear on what Prof. Vihar Georgiev works on. “One day she called me to show off: ‘I bought you an aftershave, it says it's made with quantum technology.’ She wanted to make me happy, because in her mind that's exactly what I do.”

And how quantum is that aftershave, really? Not at all. As the professor puts it, these days if we hear about quantum or nanotechnology, chances are we're dealing with marketing hot air with nothing behind it.

So what does he actually do?

You may have heard of Silicone Valley. That one is in fact near Dimitrovgrad, an industrial town in southern Bulgaria, while Silicon Valley in the US owes its name to the chemical element that has carried digital technology this far. Far enough that I have in my pocket computers capable of miracles—giving us access to all the information on the global network, connecting us by live video, making artificial intelligence possible.

A Whirlwind Start

Silicon-based chips turned out to be an incredibly successful solution, one that helped us build information technology with all its advantages and imperfections. But they are close to their limit—we already make extraordinarily refined microscopic semiconductors, transistors that stubbornly keep getting better. Plenty of people will comment on this without much enthusiasm, but the steady doubling of computing power over the last five decades is a fact no one can dispute.

We have refined chipmaking down to incredible detail. Which is why it was no accident that a few years ago we ran into the notorious shortage—there turned out to be far too few manufacturers able to make the precious molecules that form the body of our digital society.

The problem has gradually sorted itself out. And now the next huge question comes to the fore: technologically, it looks as if we have “squeezed” the full potential out of silicon chips and are fighting for the next few percent of efficiency. Hasn't the time come for the next big step, the one that will make the next great breakthroughs in information technology possible?

Major Whirlwind

Right here, in the whirlwind of events, is the moment to talk to Prof. Vihar Georgiev—whose first name, fittingly, means “whirlwind.” Though a chemist by training, in recent years he has devoted his work to the technologies for developing the next generations of chips.

Every device—our phone or our computer—now holds at least several million transistors, the miniature parts that do the calculations. If you think the topic is overrated, it's enough to mention the tensions of recent years between the US and China over Taiwan. The small island became the world center of chip development, and the business there grew and deepened so much that only a handful of companies in the world can make them.

How does Prof. Georgiev's research help in this? “My goal is to simulate devices, these transistors, so we understand how they work and how we can move forward,” he says. “Today they keep getting smaller, on the scale of 10 to the minus 9 meters, about 100,000 times thinner than a hair, and at that scale physical rules apply that are very different.”

When we're talking about units this tiny, the main problem that comes up is measurability. “Bulgarian-made Kalashnikovs keep working even if there's some deviation,” the professor jokes. “But in nanotechnology, if you have a deviation, every transistor starts working in a different way and has different characteristics. Then the chip you're trying to build from them doesn't work properly. At the nanoscale the biggest problem is to average out the parameters as much as possible, to predict how a given material will behave.” That is what makes it possible to create chips with sufficiently stable parameters.

We're All Nano!

And while we're on the subject of the difficulties of the nanoscale, it's time to mention the other big direction of the scientist's work. Thanks to the COVID madness (which we quickly forgot), we all now know what a PCR is and what a rapid test is—two ways of finding out whether we'd caught the disease that was so fashionable back then.

But couldn't there be a more effective technology? Chips that would let us judge not only whether a person has a particular infection but also their overall condition and what other health problems they have? Couldn't we take advantage here, too, of the fact that we live in the Silicon Age?

That is where another part of our guest's work is headed. “I can put some substance on the chip and learn what signal to look for. The sample may be for COVID, but I may also want to track blood sugar levels. A blood sample contains many molecules, and for each of them it's possible to work out what a given signal means, what its ‘fingerprint’ is.”

Chip 'n Dale

This is where Prof. Vihar and his team bring in machine learning, which lately we've all grown used to calling “artificial intelligence.” Ordinary data analysis proves insufficient, while the algorithms manage to judge more precisely which sign from the molecules in the samples can reveal what.

“The idea is to make a universal device that measures everything possible in a blood sample,” Prof. Georgiev explains. “Normally, for blood tests they draw blood into a test tube, sometimes as much as 200 ml. With transistors, the whole test can be done with a minimal sample.

That's because over the last 50 years we humans have perfected the making of flawless chips at miniature sizes. I believe that soon it will be possible to run every test from a single drop of blood. That a million-dollar laboratory with a machine the size of a room will turn into a biosensor the size of a phone chip. Then we'll have personalized medicine too,” Prof. Vihar Georgiev is convinced.

Turn On the Transistor!

The results are promising enough to push the professor to focus mainly on this line of development, with commercial aims. He admits that one reason for choosing this next step is the direction science is taking, which he doesn't like. He would prefer to carry on with his research without having to venture into the world of business. But in the UK—the country he chose for his career—the top priority in recent years has been military technology, which gets the most serious funding.

“Because of the war, in the UK the money now goes mostly to weapons,” the professor says. And he moves on to the other areas of research he works in. Quantum technologies that could produce a next generation of GPS navigation, far more precise and not directly tied to satellites. It uses the gravitational field, which lets it work in places currently out of reach for the technologies we know, such as underground or underwater.

But back to chips: will we manage to keep living up to Moore's law?

“Many people say we no longer manage it, because it's an economic law,” says Prof. Georgiev. “Every 18 months you have to halve the cost to stay competitive. It still holds if you go out to sell technology. With processors we're no longer talking about nanometers but angstroms, one step further down. 10⁻¹⁰ meters. We're reaching atomic precision in materials, and we don't know what comes next.”

According to the professor, one possibility is for silicon chips to be upgraded with the capabilities of graphene, as the next material that would allow the next steps. Only a few companies remain in this race today—TSMC, Samsung, Intel and GlobalFoundries—and the first two are several lengths ahead of the rest.

Change the Chip

Perhaps the most promising next step is “upward.” Most transistors so far are flat, and the big companies are working to add the vertical dimension, stacking transistors one on top of another. There are still far too many questions about how these building blocks will be built, though, because three dimensions bring their own new and unexpected challenges.

Another big direction, as has been discussed here before, is quantum computers. Our guest, an undisputed expert on the subject, is skeptical about their development any time soon. Mainly because of economic limits—so far these technologies have failed to stir the interest of the big players in chipmaking, and every new technology arrives not only thanks to scientists' successes but also thanks to economic interest. “That's the big problem for quantum companies. TSMC don't want to work for them, because they talk about 100,000 chips. Meanwhile TSMC work with companies like Apple, for whom they produce billions and billions of chips.”

Yet another of today's paradigms is biocomputers. Prof. Georgiev believes news is coming from that direction too, but in a rather different context.

Bio or Not a Computer

“If our brain is a biocomputer, it is the hardware, and the software is the books we read. We program this hardware in a specific way so it does a certain job. We have the architecture; we have to come up with algorithms. A biocomputer has to be the same. Can algorithms be devised to program a biocomputer? Most likely, yes. What problems could such a biocomputer solve? I don't know. Most likely there will be classical computers for problems that have been very well worked out over the last 50 years. And for specific, completely different solutions we'll have biocomputers, say in pharmaceuticals, simulating how molecules interact.”

And amid all this, we'll lose Moore's law, because we'll no longer be able to “squeeze” any more out of silicon chips…

“In my view, our problem is that physics and biology—nature is one,” says Prof. Georgiev. “But we don't understand this nature well enough, and that's why we have biology, chemistry, physics.”

Chip-Nosed

Is there a chance we'll understand the physics of the very small better, so that this becomes the next breakthrough letting us make chips even tinier than the angstrom scale? “Yes, there's a chance. People are trying all the time. But the thing is that as computing power grows, the effort, time and money needed for the next step grow exponentially too,” the professor says.

That's why chipmaking increasingly resembles aircraft manufacturing. Once every country had many manufacturers, but planes gradually became so complex that passenger aviation today rests on two giant companies—Boeing and Airbus. And that development didn't turn out so well when it came to the next steps. In recent decades aircraft manufacturing has achieved no breakthroughs remarkable for society; if anything, the opposite. The breakthroughs are in image and in the planes themselves.

What if the same happens with chips? What if we hand their production to two global companies that could easily settle into a showy kind of competition that more conservative, market-minded people would liken to a cartel?

“Most likely the same will happen in the future. TSMC and Samsung will produce innovations that come every 18 months, every 3 or 5 years. More and more they'll be looking for where to squeeze out 5–10 percent of a material's performance,” says the professor.

Ice Age

In the public conversation in our part of the world, we have certainly grown used to neglecting science in recent years. That's why it feels both familiar and strange to hear the professor, from the other end of the continent, from a country that even left our formal union, the European Union, talk about funding problems. About budgets going not to important areas like the next generations of chips or the chance to diagnose serious diseases, but to technologies of war…

“I think we live in the Silicon Age. Everything around us is semiconductors. Like it or not, Musk's next company aims to put them in our brains too, and it will probably succeed. Whether we want it or not, that's how it is.” But what will the era after the Silicon Age be? “Who can tell? Maybe the cyborg age. Let's hope it's not a biocomputer in the full sense of the word,” the scientist smiles…

In the whirlwind of events we don't have much time to stop and think, to discuss, to plan with foresight. And I believe we are lucky to live in the best and most interesting of times. In an era when we have to make important decisions for ourselves as a civilization and as a biological species. And where we go from here still depends on each of us.

– One of the ideas behind your academy is to get more young people into the education system. What does success depend on?

– The idea is to help people who want to step into the classroom figure out how to do it.

Teaching at a school today is more accessible than ever.

The law changed a long time ago: a person, even without a degree in education, can walk in and teach. Teachers and principals can bring in people like that and help them succeed in the school environment.

Our academy wants to help people gain all the knowledge and skills they need so they can teach with confidence. We're preparing various trainings that we'll run until the end of the year; one of them is on literacy. The teacher leading it already has a lot of experience and also teaches university students. She told me: “When I started, it was incredibly hard, because there were so many things I didn't know—the regulatory framework, the tools, how to plan a school year, a single lesson, what to do for the children, how to approach every case that came up.” Every young teacher runs into this and needs more support.

That doesn't mean universities don't cover it—students even have mandatory teaching practice—but from what I see and sense, there aren't enough tools and practices handed directly to teachers so they can bring them into their lessons.

For more people to sign up, they need to understand that being a teacher is something that can happen for them.

– What's the shortest path? Say I'm a programmer and I decide to teach—what do I have to do?

– I could recommend you to a school tomorrow, and they'd hire you on the spot.

That's the shortest path—find a school that needs someone like you.

Getting hired is easy; the next step is much more important, and that's what this is all about. The shortest path is to find a school that's ready to invest in you.

– What did your own path look like?

– When I went into a school for the first time, I already had experience training adults and running extracurricular activities for students. In my case it wasn't the shortest path, because I had 7 or 8 years of experience training sales staff; I had a background in teaching.

A friend of mine who's a teacher just told me: “Acho, we need someone to teach programming. You run extracurricular classes, let's give it a try.” We tried, and it turned out to work. And it's very

rewarding, because children are genuinely happy when they see a teacher who comes from the real world of practice.

If you have no teaching experience, I think the most direct path is our academy. In 9 months, from October to June, we'll give these people all the knowledge and skills they need to be ready to walk into a school.

I've already helped about ten people start teaching in various schools; two or three of them are still teaching. The others either lacked the knowledge and skills, or realized it wasn't quite for them. But they learned it the hard way.

Our preparation will help such a person start work as early as next September. What we'll add soon is that, together with partner universities, we'll enroll people in the postgraduate teaching qualification that many universities in Bulgaria offer. With it, you become a certified teacher in the subject of your university degree.

– What surprised you when you ended up in a school? What hadn't you expected?

– What surprised me most, perhaps, is that

I had to be not just the person who passes on knowledge, but also the one who listens, understands the students and supports them, even in their everyday troubles.

One day from my first school year comes to mind right away. An eighth-grade class walks in after some tough test. They all look tired, bored, sad. I'd planned to teach them something complicated, and I say to myself: “Okay, clearly we're not doing that.” “Do you want to play games?” Everyone's eyes go wide. “We're not doing anything today, I'll let you play. I just want you to keep it down.”

They were so happy, and the next lesson they came in so eager! They expected we'd play again, and I told them: “No, this time we're doing something else.” But because I'd listened to them, seen and understood that the moment wasn't right for teaching something new, the next time they were far more motivated to learn.

Back then I reacted on reflex, instinctively, without even thinking. Afterward I analyzed that situation a lot, asking whether it really was the right decision at that moment. And I realize that it was. Now I try to be more conscious when I make decisions like that, so that they serve the children's interests in the moment.

– Why do you think we've reached a point where the teaching profession is aging?

– In my opinion, because

for decades the teaching profession hasn't been held in the highest esteem.

When I was a student—and maybe this comes from my family—my parents always treated teachers with respect. I very rarely allowed myself anything disrespectful, and when I did, it was usually to look cool in some group. But it always made me sad.

After 2000, though, I think there was no longer that much respect for teachers. Because of lower salaries, because of many things that happened over the years.

In recent years the Ministry of Education has taken several very useful steps—it raised teachers' minimum salary, which immediately raised their average salary too. They created many tools to encourage learning and the development of these teachers, and they support principals.

Yes, it doesn't work equally well everywhere, but they've definitely taken good steps. A teacher's minimum salary is now, by definition, twice the national minimum wage. Which means that whenever the minimum wage goes up, teachers' pay follows immediately.

Right now it's around 1,500 leva (about $850) take-home; a teacher starts with that right away, no questions asked. And in a small town that's a pretty good salary.

And this isn't widely known. That's why most young people aren't interested, and naturally the profession ages. People in the system are overloaded across the board, especially math and science teachers, who take on more than the required hours. Simply because there's no one else. That's exactly why we created the academy.

– How many people need to enter the system for it to work well, be balanced in age, and have enough prepared teachers in every subject?

– Right now we have about 80,000 teachers. The National Statistical Institute gives an official figure of about 67,000, but only for general education schools; vocational high schools aren't included.

Those roughly 80,000 teachers cover, let's say, 90 percent of the need. Ninety thousand—in the perfect scenario 100,000—teachers would cover the country's entire need. It's a regulated profession; there can't be many more.

The bigger problem is that

15 percent of teachers are already of retirement age.

They shouldn't have to work if there are young people, and it's not a question of whether they want to—by law, if a person who isn't a pensioner can fill a given position, the school is obliged to hire them.

Those 15 percent are the system's huge need right now. That's 10,000 to 12,000 people. And on top of that there are another 20,000 to 25,000 who would be good to bring in.

At the same time, about 20,000 people graduate from universities every year with a teaching qualification, and far from all of them become teachers. Why? Partly, I think, because many are philologists who didn't enroll to study pedagogy. A very large share of them go in other directions—they become translators, consultants. Either way, there's a serious gap that universities aren't filling.

– How do you think we should teach technology? Every year, every month, something big happens in this field; lately it's artificial intelligence. But education is a conservative system that can't change the curriculum and introduce new things every year. How should we approach it?

– In our complete program, the first 3 of the 9 months—a third of the teaching—are devoted to digital skills for teachers. Three months focused only on that, because we believe it's crucial for these teachers to succeed in today's reality.

We believe technology should be taught within and through the other subjects, not as a separate subject.

Right now we have “Computer Modeling and Information Technology,” which starts in third grade. It teaches how to use a computer for specific tasks. To me that's very valuable, and it's important for a subject like that to exist up to a certain grade.

After that come the subjects “Informatics” and “Information Technology,” where programming is also taught. Under the national standard, HTML and CSS—the way websites work—must be taught everywhere in Bulgaria.

To me that's as valuable as history, geography, physics, chemistry. None of these subjects makes you a world-class chemist, but they make you someone who understands how the building blocks of that science work.

Once you finish school, you might have no interest in chemistry and never look at it again, but it's valuable to have basic knowledge.

Still, I think information technology shouldn't be taught as a separate subject; teachers in every subject should use it to teach. Then they'll naturally expect students to use it as well, to learn the subject or to demonstrate knowledge. That's why I think it's very important for every teacher to have digital skills they apply in their lessons, so that the students do the same.

– But that's hard to make happen, because of the system, because of the aging, and because there's a generational barrier when it comes to technology.

– We ran a training on media literacy and artificial intelligence—two elements of digital competence. How to spot fake news, handle information sensibly, check sources, and how to use the newest thing, artificial intelligence. A very large share of the teachers who signed up were older.

They were very eager to develop. I don't think age is what holds people back. Because a basic level of understanding of these technologies isn't out of anyone's reach. I don't think an older teacher would have a harder time grasping the basics and using Google search sensibly, with parameters, and showing students how to get to the right information quickly and easily.

These older teachers say their students are interested in these topics. They're not struggling with themselves, but with keeping up with their students, which is very sensible and very valuable.

The barrier is similar to the one with math. Lots of friends tell me they're not good at it; the bill arrives and they refuse to work out how much they owe. It's absurd not to be able to add up two or three numbers. It's running away from responsibility in one form or another.

I think it's the same at school with digital skills. They're something anyone can take on. Especially that basic level—absolutely every teacher can do it.

– As long as they have the desire and the energy to grow. You mentioned artificial intelligence—have teachers gotten used to the idea that it's not just something that will write homework, but can also be useful?

– The way we've built our training, we first tell teachers about the AI tools that help students. I say: “Students can use AI this way and that way. And—surprise!—they're already using it like that. If you give them this kind of homework, artificial intelligence can write it.”

First I even try to reinforce their impression that AI might be something bad, pushing it to such an extreme that they say: “Fine, so there's no getting rid of it—what do we do?” So they reach the realization that they need to know what this technology is.

Then I start showing them tools that help the teacher. The concept is that AI is a very smart neighbor you have no visual contact with. There's a door, you slip notes under it, and he slips others back. He's very smart, but he has no idea about you, he's never seen you, yet he can do very good things. You have to give him enough context, tell him what your goal is, so he can help. If you tell him, “Solve the problem my math teacher gave me,” he'll solve it without asking.

Whereas if the teacher sets the task so the student has to explain the solution—okay, you have a solution, but I want you to walk me through it. You wrote an essay; tell me why you reached these conclusions?

You can tell very quickly and easily whether a student has their own reasoning about it or is using an AI tool.

By the end of the training, I arrive at the point that artificial intelligence widens the gap between teachers who simply take some material and pass it on to their students, and those who really think, understand, and want to do something more with that class, with those students.

We finish the training with the “flipped classroom” tool. Many teachers tell us they worry that kids write their homework with AI. Don't give it to them as homework—give it to them as preparation for the next lesson. Give them the same tasks before you've taught the material. They'll find the answers, 50 percent of which will most likely be wrong, but you'll have room to discuss why they're wrong and to teach the new material after they've already used the “super cool AI tool.” And you can easily refute it, simply because it solved the problem wrong—2 plus 2 doesn't equal 5. I believe this can work in almost every subject.

– I don't know if you came across my experiment—I competed against ChatGPT to see who would score higher on the matura, Bulgaria's school-leaving exam, in Bulgarian language and literature. We both got pretty good grades, but I beat it by a little. There was an extra task: the examiner had to tell which answer was mine, and he managed it because of the literary interpretation essay.

– Even if it can write a good enough essay, I don't think that's bad. If that happens, we should start thinking at the level of the system.

Okay, until now the teacher has asked the student to write an essay; now there's a tool that does it.

Then the teacher can ask the student to build a set of such essays and find the similarities and differences between them—which AI can also do. But the analysis that happens afterward is a skill you need very often in real life. You see a huge amount of information and make connections; that's how the brain works—it tries to extract meaningful information from that data.

Fine, AI can do one of the tasks. Give the child 10 such tasks! Let them solve all 10, draw analogies, connect the ideas, understand why—or use 10 different AI platforms and see what the similarities and differences between these models are, why that is, what data they were trained on. That gives you the next tasks, which can do the same job as the literary interpretation essay.

As I understand it, its purpose is for the teacher to find out whether a student has understood what they're interpreting—whether they've read it, whether it has passed through them, whether they interpret it in a meaningful, logically coherent way.

– And whether they can express themselves fully.

– Expression is precisely what may be hardest. When you have a tool that can produce your means of expression for you, you lose interest in developing them, which means you may stop having them. Maybe that's where we need to think about how to improve the approach.

– When ChatGPT appeared, Bill Gates said it was a revolution precisely because of education and healthcare. Simply because a huge part of the world that never had access can now have a teacher or a doctor. Do you think big changes are coming to education because of AI?

– I don't think huge, revolutionary changes will come. Just as they didn't come after the introduction of the computer. There are evolutionary changes, a lot of good things are happening, but they're not a total transformation.

Gathering a group of children with one or more adults to do something together won't change, in my view. It will remain the way to consolidate or focus on a specific element of knowledge, skills or attitude.

Rather, what AI will help with, as I said, is flipping classrooms. First, so they're no longer: “I, the teacher, will now tell you, the student, what you need to know!” Good teachers don't do that now anyway, but it will simply disappear.

The setup where the teacher stands at the front and the children look at him will be turned around. Lusio Architects is a Bulgarian studio that designs schools, and they have many successful examples of how a learning environment can be shaped. It doesn't have to be children looking at each other's backs with one teacher at the front; it's more a space that can be rearranged. Small groups working on a task; a big circle for discussion; something happening in one corner, something else in another. Changing spaces that still let one or more adults with a larger number of children carry out some process.

That won't change. The physical need for these people to come together won't disappear, at least not because of AI.

It might happen with virtual or augmented reality, but that technology is still less developed.

– But we shouldn't underestimate it either.

– I think all of this will help such revolutionary educational systems emerge. I have an idea for one. The school year doesn't have to run from September to June—9 months of going to school every day and doing something specific, followed by 2 or 3 months of vacation.

A revolutionary system like that certainly won't be the mainstream way of learning, but I believe it will be very valuable for some. Children need rest, but not 2 or 3 months bunched into the summer. I imagine the year could be split into three four-month blocks, each with three months of learning and a month of rest.

And this learning doesn't have to happen physically in one place. For two months, assignments are prepared and students work remotely, being given the hard material they need to understand, learn and prepare. For one month there's intensive teamwork, where they physically gather in one place to put it all together.

With technology, this can be done very well. It requires a drastic change in the daily lives of parents, teachers, everyone, but I think it would help students who need more independent time and fuller rest. Without 3 months of vacation after which they have to start over.

– Quite a few new phenomena would help—remote work, for example. And again the problem is that we're talking about a very conservative system. I've also interviewed a teacher who has never set foot in a school. There's so much we could change and develop. The current school year was designed around farm work—so children could help out until September 15. Things change slowly and with difficulty…

– I think we'll see revolutions of this kind. And at some point, not necessarily because of technology, there will be successful examples that get applied more and more, even in the more conservative view of education.

And why is it conservative? I think about it in the context of why private tutoring exists. Parents want peace of mind that translates into: “I'm sure this child can handle a given exam.” It might be the matura or a class test. There are many specific moments when knowledge is tested, the child has to give 100 percent, and if they fail, it can have a very bad effect on their long-term development.

The system is conservative precisely because if something changes, it could be bad for an entire generation.

Even though the pandemic showed very clearly that overnight we switched to online learning, which is a fundamental change to the entire education system! And it turned out to work. Maybe not at 100 percent of what it would otherwise be, but it works. We'll see more and more changes like that.

– Interesting changes are coming because of technology and artificial intelligence… And I'll take the opportunity to invite you—and all readers—to take part in an important survey about our attitudes toward it, here. Thank you, and I hope many talented future teachers sign up at Sindeo!

– You took part in the discussion about why it is worth doing science in Bulgaria today. Afterwards I watched some of your interviews, and they always ask you: how come, why did you come back? Why do you think it sounds so strange that someone who could work at Oxford chooses to “dig out” a lab in the middle of Studentski Grad, Sofia’s sprawling student district?

– I really don’t like that line of questioning. I keep getting asked it because we grew up in the 1990s, when

the media constantly repeated that every capable person should leave for somewhere else.

So now, when some people come back, everyone else is surprised.

I don’t like it when this topic comes up. You see, it’s as if I’ve arrived here and the red carpet has to be rolled out for me.

It isn’t a sacrifice. Look, for me it was simply better to come back. Because if I had stayed abroad, I wouldn’t have had any real chance of a permanent job, of steady development. There, in science, you’re on temporary contracts, one year at a time, you plan year by year, and you need a lot of luck for a position to open up at a university. In The Big Bang Theory, whenever a professor died, everyone would say: “Now there’ll be a tenure opening.” That’s what they call it abroad when you get a chance at a permanent career.

My option was to stay on as a postdoc, one year here, one year there. People who keep moving around the world until they’re 45 or 50.

– Still, it’s Oxford, that’s where big science is done.

– I don’t want to talk about Oxford. Last time,

when I said that I’m better off here than there, there were comments under the piece saying they only pick the best, he isn’t good, that’s why he didn’t stay.

They did offer me a chance to stay; they had a new project. They’re still developing what I worked on there, they’re even commercializing it. My contribution is very small, I don’t want it to sound as if I left them something tremendous. I just didn’t want temporary contracts. I didn’t want my whole world to fit into one suitcase at 30, knowing that soon I’d pick it up and move on to the next university.

– Isn’t that system a bit broken, if it turns away people like you?

– You have to stay motivated, to fight, if you really want it, but in the end you wonder what for. Wherever I go, if they offer me a permanent contract, the science I develop will be their projects. In other words, I’d have to invest myself in somebody else’s ideas. Whereas here I have the chance to develop my own ideas, to apply for funding, to build my own lab, and in that lab it’s just me. The one-man group, as I joke at conferences. And that’s the big advantage.

It’s possible here because there isn’t much competition. At Oxford, if they post an opening, they’ll get dozens of applicants from all over the world who don’t know why they’re applying, except that it’s Oxford and they want to be there. And that distorts things a little. Their system, where you get competition, selection and sorting, doesn’t guarantee that the best person really ends up in the position. I’m not saying it out of sour grapes. I just think the criteria they use are somewhat subjective.

– Isn’t science done in big teams? What can a single “one-man lab” achieve?

– No, I don’t work alone. I collaborate with Sofia University: with Assoc. Prof. Nina Kaneva, we started working on nanotechnology back as students, in 2007. Now we have a project with the Bulgarian National Science Fund, KP-06-N59-11. A code worthy of study by numerologists, but with that combination Nina and I hit a career restart in science, and it helped me build my lab. I also work with the Bulgarian Academy of Sciences; at first it took me time to make contacts and find good people. And I work with colleagues in Sweden, in the group of my former supervisor, who really wanted me to come back.

I simply decided I was better off here, so that I could develop my own ideas.

It was a bit hard at the beginning, around 2018, because there was nothing. But now I have all sorts of things, from a 3D printer to a milling machine. You start with small steps, from zero, you attract funding, you buy equipment bit by bit. That’s how the ball starts rolling, grows bigger, and eventually I have enough to do what I used to do before.

– What exactly do you do?

– I work on depositing thin layers of various materials that can absorb light. They’re about 100 nanometers thick, 1/500 the thickness of a human hair. The material is transparent, but it can absorb ultraviolet light and turn it into chemical energy.

One application is self-cleaning surfaces. If I coat my glasses, which are always getting dirty, with this layer, then when I go out in the sun all the greasy smudges will break down on their own. It’s also used in solar panels. Over time dirt builds up on them and lowers their efficiency, and cleaning them is very difficult. Besides, with the method I’m developing, such layers can be applied much more cheaply, without the vacuum deposition the industry uses now.

Building on that, we moved into other things. We worked out how, with the same technology,

to make small electronic circuits on glass.

We also decided to test whether they would work as sweat sensors. Say we want to measure whether there’s some protein in sweat that serves as a marker for a disease. I’ve made humidity sensors this way too, and now I’m making heat sensors.

– I’ve been writing about science since 2004, and back then so many experts said nanotechnology would be everywhere within ten years and change our lives, the way people talk about artificial intelligence now. Why didn’t anything like that happen?

– Every ten years or so there’s something like that, which turns into a marketing tool.

There are plenty of examples. When a hot topic like that appears in science, everyone starts working on it: “I’ll write that I make nanostructures when I apply for money, it’s a hit right now and they’ll fund me more easily.” That’s how it was 20 years ago, and then it passes into marketing.

Now it’s happening with artificial intelligence. All the companies that make windshield washer fluid would have written back then that they use nanotechnology, and now it’s AI. I’ve often wondered, reading a label, what exactly nano-micellar facial cleansing water is.

Quantum computers, 3D printing… All extremely

flashy topics for research, and in the end there really aren’t many applications that change our lives.

I definitely think it’s about marketing.

There are some examples, of course. Self-cleaning windows are already in use: the two largest companies in the industry offer that kind of architectural glass for all the tall buildings where architects decide to wrap everything in glass. But still, unfortunately, in science just as in marketing, there are these keywords, these hooks, that change periodically…

– And why is chemistry somehow off the media’s radar? I can’t think of any big news in recent years. Physics, say, or computer science get talked about far more.

– That’s very interesting, the difference between chemistry and physics. I’ve always felt somehow proud to belong to the minority group of chemists, but I also feel we’re underrated in terms of our usefulness to society. If you think about it, physics grows out of philosophy. So way back, 2,000 years ago, that’s where it all started.

Whereas chemistry—we had alchemy, which was closer to the spiritual, and it was harder to understand what exactly they were doing. It didn’t find applications; it was mostly craftsmanship. Chemistry really starts from metallurgy.

It’s simply more applied, and that’s why I don’t think it generates big news that interests the media.

– Society somehow has the impression that everything in chemistry has already been discovered. Sorry for the sweeping generalization, but that’s how it seems to me.

– If you think about it, whenever a new chemical element is synthesized, one that has practically no use whatsoever, it’s always news. Because there’s an element of a race there. The two ends of the world compete over who will come up with the next one, who will manage to synthesize it. When they succeed, there are no applications.

– The notorious artificial intelligence we mentioned—does it have applications in chemistry? Are there places where it could lead to a breakthrough? For example, in generating new materials much faster…

– I have colleagues who use machine learning to predict the properties of substances. I see it more and more in scientific papers too: “Our group used machine learning and predicted that the material with optimal properties for a given application will have composition XYZ. We haven’t made it, we haven’t tested whether this material will really be that useful.” In my view, the goal is to make the paper stand out, and again it’s mostly marketing.

I graduated in computational chemistry, and the main thing they trained us for was how to use simulations to predict the properties of substances. Honestly,

however attractive it is to put “artificial intelligence” in the title of a chemistry paper, I don’t think it’s all that successful.

About 20 years ago there was something else, called QSAR. The idea was that if you’re the pharmaceutical industry and you want to make a drug, you know what the molecule should look like, but you have several thousand variants and you don’t know which will be the most active. What they did was similar to machine learning. They synthesize a few variants, the most extreme ones, measure some properties, feed them into a computer, build a statistical model, and then for all the remaining 2,000 variants you can predict what the effects will be.

– But just weeks ago Google announced a new model that will create new materials extremely fast, and that this will let us advance computing very quickly. You’re rather skeptical.

– It’s just not new… Computational methods in chemistry date back to the 1970s. If I studied computational chemistry at Sofia University in 2007… that’s exactly what we were doing in practice. The goal wasn’t to predict, to create a new material purely on the computer, but for the computer to help us explain where the properties of a material come from, what structure it needs in order to do the job we expect of it.

Developing new materials is cheaper and faster on a computer. But unfortunately it turns out it’s not always quite right. There were many publications, even in Nature, where they used machine learning to predict candidate materials for, say, lithium-ion batteries, with a better weight-to-capacity ratio. They predict which is the best of 5,000 variants, but in the end it turns out that when it’s actually synthesized, it doesn’t do the same job.

And the problem is that

this way of predicting, of synthesizing materials on the computer, is only as good as our understanding

of the relationship between the structure and the properties of materials.

– Except the idea is that the algorithm will be more impartial than we are.

– But it will be based on what we know. Say I know that with a copper-zinc alloy I’ve measured the density and the electrical conductivity at three different ratios. I’ll ask the computer to predict an alloy in which the two metals are in the best ratio to give me a certain resistance, and that computer will rely on the five points I’ve measured. In other words, my understanding of reality may be wrong.

AI and machine learning are useful for chemistry. Yes, you could say everything in chemistry has been discovered, but very often it turns out that the things we believe we understand are only an approximation.

I tell my students about this too. At the end of the 19th century there was a lecture at the Royal Society in England where a lord declared that

we now know absolutely everything about the world, down to the smallest element.

We know there are atoms and nothing new will be discovered. Yet a few years later they go and discover the electron, then the proton, then that there are other things inside the proton. In the end it turns out our idea of the atom was completely wrong.

– We should even change its name—it comes from “indivisible.” And we still call it that.

– Not only that, we went through three stages. First we had the model of a single positive mass with electrons floating in it, the “plum pudding model.” Then Rutherford discovered that the nucleus is very small, it sits in the center, and the electrons orbit around it. Then Schrödinger came along and complicated things even more.

So there are things we still don’t understand. Only well enough to use them in practice, but I think that when it comes to the fundamental questions, there’s still a lot left to be desired.

– What do you expect to happen in this direction in the coming years?

– My topics, chemistry’s topics, go only as far as the outermost electron shell, as physicists like to joke. I don’t know what to expect. But I’ve noticed that in recent years the Nobel Prize in Chemistry has increasingly gone to people who don’t work in chemistry but in biochemistry. Maybe materials science isn’t that attractive at the moment.

– You’ve been popularizing science for a long time. How do you think we can make it more appealing? Should we have science influencers?

– I’ve stepped back a bit from those topics; in recent years I’ve focused on the lab and on getting projects moving.

– But the trends are the same. And you meet young people, you teach them.

– When I came back to Bulgaria, I spent some time at Sofia University too, but there was no chance to stay there, so I ended up at the Technical University. And I discovered that it’s an incredible plus to teach chemistry to people who are engineers. For them chemistry is something they don’t believe they’ll ever need, and they didn’t pay much attention to it at school. But when they come here,

and I try to present it to them, I notice how impressed they are by how interesting it actually is.

When I see that someone finds what they’re doing interesting, and I can hold their attention for 45 minutes before they do the experiments themselves, that gives me real pleasure.

As for science influencers, there are quite a few good YouTube channels that show science. I’d say some of them may even do more interesting things than what I’ve seen colleagues do in labs. Breaking Taps is one example: a YouTuber who has a scanning electron microscope and an atomic force microscope, equipment some universities don’t have, and makes interesting videos. In one of the latest, he showed how he built something like a primitive sensor on a piece of glass, like the ones I make here, a matrix that captures images.

My problem is that these more specialized channels would mostly be watched by people like me. Whereas

some of the general-audience science channels sometimes give misleading information.

Veritasium, for example, is hugely popular, but sometimes slightly misleading.

The reason is that when you lean more toward being an influencer than a scientist, you’ll try to make what you present more attractive, and you’ll lose some of the science.

– Those are very strong examples. But in Bulgaria I don’t think we have anything that comes close to either direction. I think that’s somehow a function of society’s overall interest in science.

– If you ask society, people are very interested in science. Everyone watches National Geographic, Discovery… I think in Bulgaria we have yet to develop this kind of science content.

When I read books, I buy them from an online bookstore; I don’t set foot in physical ones at all, and the reason is that in my first years back it really traumatized me: I’d go into any bookstore, reach the science section, and

50 percent of the books there were esoterica, even though there was a separate, much larger esoterica section,

with the memory of water and all sorts of other topics like that.

People find that interesting, I understand, but if you take it as an example… It’s easier to get people to listen to how aliens visit us than to how hair dye or sunscreen works, where the chemistry is in that.

When it comes to chemistry in particular, people are wary. I think it still sounds scary. And boring. At school I didn’t find chemistry interesting either. With many subjects, my problem was that I didn’t understand why we were studying them. It only became clear to me much later. I think something similar will happen, slowly but surely, at the level of society too.

What if we turned the stereotype of artificial intelligence on its head? Instead of a single model we chat with, we face countless separate “individuals.” We hand them tasks, and each works autonomously, specializes in a particular job, accumulates knowledge about it, keeps an eye on the others…

The goal might be, say, to build software. One model learns to formulate the requirements, another writes the code, a third prepares the visual side, a fourth tests what came out and how… and so an entire software company comes together, working millions of times faster than ordinary ones, because it is built not of people but of algorithms.

How far off is that future today?

Not long ago Sam Altman said that this is exactly the direction in which very serious breakthroughs are coming. AI agents are one of the fields of computer science where we expect big news. The next generations of artificial intelligence, able to solve far more complicated and complex tasks while making far fewer mistakes. Many of the leading experts say this is the approach by which we will take the next big step in the development of artificial intelligence. Here is why.

Many Hands Make Light Work

In our part of the world, “agents” remain those mysterious figures who set the political agenda from the shadows—the informants of State Security, Bulgaria’s communist-era secret police. Never mind that 35 years have passed since they last “snitched”: hardly a month goes by without yet another list of files being published.

These agents are entirely different. They are the good guys, like their colleague 007. We are talking about a different concept of how to use artificial intelligence as fully as possible.

Have you ever considered that a… secret agent is roaming around your home? If you own a robot vacuum cleaner, for instance, it meets the criteria of an AI agent, and there is no question it is secret—after all, it never introduced itself as one, did it?

But relax, you won’t find it on the next list from the Files Commission, the body that unmasks former State Security collaborators.

It does, however, fully fit the definition of what an “AI agent” is. Yes, it may be a long way from the complex-task scenario we started with, simply because it sits lower in the hierarchy of such systems. AI agents come in quite different types. Some are already around us, but the more interesting ones are the others—those that will be able to carry out the scenario we began with. To solve complex problems.

Freelance Informant

The obligatory short definition: an AI agent is an artificial intelligence program that has been given a specific task. It can be physical, like the vacuum cleaner mentioned above, or purely software. And the other obligatory condition: it must be able to act autonomously within certain limits. Just as the vacuum cleaner decides exactly how to make its way around your living room, but would never go beyond the boundaries you have set for it.

One of the intriguing directions of development is personalized agents. Our own personal superhero, able to help us with so many and such varied tasks. Of course, the future looks quite thought-provoking and motivating once we have the perfect personal assistant. Our very own Jeeves or Watson… or perhaps a personal copy of ourselves, trained to resemble us as closely as possible. Another Georgi, to whom I could delegate only the boring tasks and those I think he would do well. Writing these pieces I would keep for myself, at least for now. (I’ve tried it—it’s fun.)

For the moment, in any case, the development of AI agents that perform a specific, strictly defined task is much further along. One recently unveiled agent, Google DeepMind’s SIMA, specializes in 3D video games. Trained on a given title, it becomes capable of handling some 600 skills—from navigating the game to clearing even the hardest challenges. But… if we delegate the very playing of games to algorithms, what will really be left for us?

Stierlitz

When it was announced, the Devin system was a hit. The namesake of a well-known Bulgarian mineral water promised to do exactly what we began with—to create software with the help of agents. Its unveiling became huge news in the software world. This was a pioneering development in the field, one already ready to take on a full 13.86 percent of the work… which, in such an expensive and highly specialized activity, adds up to quite a lot of money saved.

You simply give it the task and it does everything else—from the concept of how the program should look, through the architecture, the writing of the code itself and the tests for it, to the testing. The demonstration was more than impressive, because it really did look as if the first “AI software engineer,” as its creators called it, could take the bread out of many people’s mouths.

Yet, at least so far, there has been no word of the system entering widespread use. Most likely it has still turned out to be more expensive to have software specialists check and fix everything that didn’t go as it should than to build it themselves.

Still, let me say it again: this is a pioneering development in a field where progress happens extremely fast. It is enough to point to the speed with which algorithms learned to create images. Or the opposite—there are areas where progress seems to have stalled.

Recently the well-known researcher Andrew Ng wrote that, in his view, AI agents are the next big direction in machine translation. Because they can easily work on several levels, agent after agent assessing how well the previous competitor has done and improving on its result.

Hand in Hand

Of course, the idea is by no means new. GANs, the networks that were the first to prove capable of creating human faces indistinguishable from real ones, work on this principle: one neural network aims to generate, while the other works to judge how well the first has done.

And yet the next step became possible with the development of large language models in recent years. Ventures began to swarm that let a person build a small army of agents with all kinds of goals. For example, harnessing several instances of ChatGPT to talk to each other in search of a solution, debating until they reach a consensus. Here is an approach in which the answer to a given question would be much better and largely free of the great flaw of this type of model—hallucinations.

One example of such a tool is AI Agent, an app in which you simply pick a name, assign a task to your AI agent, choose a GPT model for it to use and watch the result. Minimal programming knowledge is needed, and soon it will probably be possible without any. Another popular project offering similar possibilities is AutoGPT. And BabyAGI too… but wait, a baby artificial general intelligence—are we really that close? We’ll get to that as well.

Miss Congeniality

Unlike a chatbot such as ChatGPT, agents don’t need you to keep sending them questions, instructions and assignments. In this approach they work until they achieve the goal set for them or hit a given limit. That is precisely why today’s heroes are considered the next step in the development of artificial intelligence—because of their independence.

AI agents become a powerful weapon when they have the opportunity to improve, to learn. Yes, our vacuum cleaner also has a sophisticated artificial intelligence that knows the optimal way around our home, but all of that happens within given rules. If an agent we ask to work as a journalist can improve based on feedback, if over time this makes it better at its tasks, then things become not only interesting but limited almost solely by imagination…

Welcome to the first virtual town! A year ago, researchers at Stanford University used OpenAI’s models to create an entire “settlement” inhabited by 25 virtual agents. Each had basic memories and a personality, and they were set loose to live their software lives in their virtual town—something like a video game. The 25 were given names, ages, professions, families, interests and innate habits. From then on they were left to interact without any additional instructions, guided only by the large language model.

The Files Commission

The result? Gradually each of the “people” developed a character of their own; some even fell in love and wished each other a happy Valentine’s Day. In the end, what emerged was something resembling a real human society—the characters communicated, remembered information, reflected on their experiences and made plans for daily activities.

That is why agents are thought to be extremely useful for the next level of simulations. With their help we could, for instance, study different forms of interaction many times faster than science does today.

I have already written about the dispute between the “structured” and “unstructured” approaches to developing artificial intelligence (here and here). According to many experts, we are already close to the limits of large language models in their current form, and either they have no way of leading us to the much-vaunted artificial general intelligence, or they will, but at the cost of very serious dangers.

Well, for some scientists the solution lies precisely in developing more advanced AI agents. They can have different architectures and even follow entirely different ways of interacting. But they complement and check one another, showing only their strengths. And in this way they lead us onward, toward an artificial general intelligence that will surpass humans, the next step toward a possible singularity.

The X-Files

And if everything so far sounds rosy, the concept naturally comes with its risks. Because the more activities we delegate to technology, the greater both the responsibilities and the risks become. As the analyst Reece Hayden puts it, on top of the problems already inherent in generative AI—hallucinations and bias, for example—agents could be capable of even more mistakes.

“When you give them the autonomy to iterate, to change their answers, to respond to feedback, this leads to far more serious and deeper hallucinations. The tasks become more complex, and every small mistake can lead to further, much bigger ones.”

He expects that in three to five years we will already see widespread use of automated AI agents carrying out complex operations from end to end.

A Past as an Informant

Another risk, which Google DeepMind researchers warn about, has to do with ethics. If even today it is increasingly easy for us to perceive ChatGPT as “something like a person,” the additional anthropomorphizing that comes with agents, the ever more personalized service, “could make people much more vulnerable to inappropriate influence by the technology.”

“AI assistants could radically alter the nature of work, education and creative pursuits, as well as how we communicate, coordinate and negotiate with one another, ultimately influencing who we want to be and to become,” the authors write in the paper.

And so, as it turns out, advanced AI agents are already knocking at our door (only metaphorically, for now). Perhaps the moment when that knock leaves the metaphor behind won’t be so bad after all? We could use this kind of technology for so many interesting, unexpected applications. To free us from so many tedious tasks, to help us advance science. As long as, this time, as never before, we hold the important conversation in time. The one we never seem to have time for, and the reason this site exists. About technology, about the way we use it. About the way it often imperceptibly and irreversibly transforms our lives…

– In recent years, especially before all the noise around artificial intelligence, ideas about a breakthrough in creating virtual reality were very much in the air. Now that people talk about these topics far less often after Zuckerberg’s ambitious plan for the metaverse, does that mean we’ve hit some kind of barrier?

– Virtual and augmented reality are parts of the telecommunications process. With the metaverse, the talk was that you wouldn’t have to go anywhere, you’d be able to communicate with everyone from home, to attend events. Behind all of this lies an enormous, very heavy and complex telecommunications process, which we call “holographic communication.” The goal is to use these technologies—virtual and augmented reality—to achieve full-fledged communication between people in different places, exchanging every kind of information in real time, spoken and visual.

The original idea was for holographic communication to replace the messengers we use every day. Today we are close to that—Microsoft already offers a similar option in Teams, as long as you have the right technology. Apple drew attention with its new Apple Vision Pro headset and added a new term, “spatial computing,” as if there weren’t already so much terminology—virtual, augmented, mixed, even extended reality. It’s easy to get confused, but all of them share a single task:

to reproduce the real world as realistically as possible, with no delay at all, to merge the real and the virtual.

That includes not only static objects but the person too. And not just as a figure, but as gestures, facial expressions, even their emotional state. For us to speak of communication and a communication process, you need a sense of yourself, of presence and of connection with the person you’re talking to. That means glances, gestures, handshakes, engaging many senses.

– What steps in that direction are you developing at the Technical University?

– We have a large team of students who have been working on this very enthusiastically for several years. For the fourth year now, we are also running hands-on sessions with students from engineering high schools. We show young people in the 10th and 11th grades that new technologies are being developed in Bulgaria. We have high-level research publications in very well-known journals around the world. We partner with American universities such as Princeton and Purdue, more than 10 universities in England, and with Japanese, Thai, Indian and Pakistani colleagues.

The problems we face in developing virtual and augmented reality are fairly familiar. The equipment still isn’t at a price the average person can afford—you need 7,000 to 8,000 leva (roughly $3,800 to $4,400) for an augmented or virtual reality headset, so

most people haven’t experienced anything like it firsthand, but the progress is remarkable.

Virtual reality is a bit more accessible, but in most cases it’s used for computer games. And that is one of our country’s strengths within the EU: we have very strong companies here, and combined with specialized education, this turns us into a sort of hub for game development.

Yes, right now everyone has thrown themselves at artificial intelligence, and with good reason. But the outlook for people who want to study and work in creative 3D technologies is decidedly very optimistic. Gaming, augmented reality, virtual reality—these are fields with a huge hunger for talent.

– Tell me about some interesting projects with which your students have impressed you.

– Many of them build applications they actually need, for example creating three-dimensional models of real objects. We have

an entire internal combustion engine, with all its components.

Projects like that are very useful, because one of the target tasks of the Technical University is developing electronic distance-learning materials. One graduating student recreated an entire lab exercise on signal measurement in virtual reality, and now every student can use it.

Another student built a virtual fitness trainer. An avatar that coaches you, follows in real time how you perform the exercises and then gives you recommendations. A “virtual coach”—you might not need to go to the gym at all. We also hold events about space; one of our students graduated in France, and with her project you can take a walk on an asteroid.

Students from abroad come here for internships, and in 15 days they manage to build their own augmented reality applications without any specific skills or knowledge. Anyone who decides to, without even a programmer’s experience, can now make something basic. The only limit for virtual and augmented reality is imagination.

– And yet we still seem far from the perfect metaverse…

– The fact that the metaverse didn’t take off with such force doesn’t stop the development of the technologies themselves, which is truly astonishingly fast. It’s no accident that the white papers on 5G and 6G identify virtual and augmented reality as one of the fundamental things these new communication technologies are built around. Right now there is active work on having enough computing and communication resources for us to fully experience virtual or augmented reality.

The movement is constant; the topic isn’t losing its relevance. With this drive to engage all the senses, haptic suits and gloves have already appeared at affordable prices. People can shake hands, pat each other on the shoulder, hug.

There is work underway, and in two or three, five years at most, it will be possible to transmit taste—

to see the little cake in the metaverse and taste it.

Smell turns out to be the hardest to reproduce, but we may manage that too. At least I believe we’re moving forward quickly.

– The ideas about virtual reality go back to the days of Jaron Lanier; we’ve been trying to create it for 40 years now. And it seems the main goal is still realistic visual recreation. Why is it so hard?

– In my experience, at least, one of our challenges is the human face. Nothing else is as problematic as the micro-expressions, the naturalness of the gaze, the movements that are very hard to capture and reproduce in real time. If it’s more static, it isn’t so complicated, but a person never stops moving, sending signals that we don’t consciously register but still perceive. That’s one of the things holding us back; it’s no accident people laughed about why everyone in the metaverse exists only from the waist up, with no legs.

The challenges are many, but let’s not forget there’s also apprehension. We easily imagine the scenario in which people forget how to communicate in reality, because everyone will be logged into the virtual world, as in science fiction.

You put on the headset and the suit, and you don’t live in the real world but in the virtual one.

That’s why this kind of technology is adopted a little more slowly, with more difficulty. We humans are peculiar: on the one hand we want and seek the best, and once we get it, we become suspicious. Since even believing that the Earth is flat is coming back into fashion, evolution clearly doesn’t always lead us only forward.

But this is what I tell my colleagues too: as engineers, our task is to improve the world, to make it better than it was when we were born into it.

– Can generative models help us in the search for this realism of faces?

– Definitely. Colleagues who were at Carnegie Mellon worked on generating photorealism, with synthetic data. That’s one of the trends,

thanks to the models, being able to generate objects,

so that everything becomes faster and the whole virtual world can be built.

But something important I want to point out is that very few people actually understand generative models. The foundation underneath is terribly complex, and for a task like this it’s important that they not be mere black boxes—that we understand well how they work. With these models, even their creators can’t always understand why the result they get is exactly what it is.

That’s something that worries people—that you have no control. That’s why I’m glad I work with specialists who dig in and try to grasp the meaning in depth.

– Do you think it’s possible to achieve indistinguishable virtual reality in the foreseeable future?

– Oh, yes! I’d even say much sooner than five years. Quite a few companies are working on it, including the very biggest.

In my view, we are very close to an absolute replica of our surroundings in the virtual world.

It seems to me that for now it isn’t more widespread for those two reasons—people are apprehensive, and the cost is still high. But I think both will soon fall away.

– What are the most important questions we need to answer before then?

– There’s a lot of discussion about how we humans behave, for example, in the metaverse. That is already a matter of ethics. Technologically you can impose restrictions, but that isn’t enough. Everything connected with technology raises ethical questions. Because we are human beings, and it isn’t always clear how we’ll react.

But I see that today’s young people think differently, their values are different, and that matters too.

When we were young, the world wasn’t in our hands; I had to go to the library, search, read, write. Now I just click and all the information is in front of me, which automatically changes one’s entire worldview.

For me, that’s the limiting factor—the ethical questions, which have to be resolved very carefully so that they don’t restrict the rights of the majority of people while at the same time protecting them.

We’ve seen bad examples of things happening in the metaverse to women or minority groups. These are problems that emerge only afterward, which there’s no way to plan for. For instance, we didn’t expect it would be such a problem for people to invade your personal space while you’re in there. It turned out there needs to be some kind of protective circle—but then if you want to shake hands with someone, what do you do?

The technological questions, we will solve. Sure, there are certain limitations that can’t be overcome right now, but options are being sought with new technologies. How will you overcome human nature? That is the hard question, which many people will be solving, and few of them will be engineers…

Can we predict the future? Not a chance, since every small step can change the direction. But is it worth trying? I think it is essential: however far off our ideas may turn out to be, the very act of looking, the attempt to make sense of it, is the first step toward preparing for it. Toward avoiding some of the dangers.

Will technology make our lives easier, or will it trigger a huge crisis by shaking up the job market? Will we enjoy the fruits of advanced artificial intelligence that has helped us dramatically extend human life, explore space and develop the next technologies? Or will we wake up in a world of total control, as predicted by the dystopias?

What will life look like in 2050? It is time to peek into the future and discuss the fascinating forecasts of an author who has the courage to make predictions in such a dynamic period of history. And he has already done it once, with enviable success.

The Earth as a crystal ball

Hamish McRae is a journalist, and, as the publisher Philip Graham put it, “journalism is the first rough draft of history.” The Briton has more than 40 years of experience, and his main beat is economics. But also forecasting. In 1990 he published the book The World in 2020. He foresaw the problems facing American liberal democracy, embodied in the election of Trump as president, and predicted that within that period Britain would leave the EU. In his own peculiar way, he even foretold the COVID pandemic. True, as he himself admits, he did not do quite as well when it came to technology.

Technology, however, takes up far more room in his new book, The World in 2050, published in Bulgarian by Knigomania in a translation by Ilia Iliev.

McRae digs deep into international politics and economics. He prophesies that in 2050 the EU will look more like a museum than a laboratory for developing modern ideas. He predicts that not only China but also India will overtake the United States as the world's most productive economies. And that Western people will, to a greater or lesser extent, have to learn from Eastern ones to put the interests of the community above those of the individual.

He makes many fascinating forecasts which, as he writes himself, are more of a template meant to get us thinking. And they are worth reading, even if only to disagree with them. Here are 10 of the ideas in his book that relate specifically to technology and to the way it is changing, and will change, our lives…

1. Being able to is one thing…

“Forecasting new technologies is much harder. We simply cannot know which innovations, currently considered bordering on the absurd, will one day really change the world, and which will hit a dead end as they are developed further. The fact that something can be done does not necessarily mean it would be of any practical use. Or its cost may turn out to be so high that it cannot be applied on a mass scale. There are, however, many areas of social life and the economy that are simply crying out for new technical solutions.”

“The difficulty in forecasting revolutionary changes also lies in the fact that once they have happened, they seem so obvious—how did no one think of this before?—but before they appear, we cannot even imagine that such a thing could exist.”

“Wanting is one thing, being able to is another, and actually doing it is a third and a fourth.” Yes, Nikolay Haytov, the Bulgarian writer famous for his earthy mountain tales, did not have technological progress in mind, and these days he would hardly lure readers with a story called Mazhki vremena (Manly Times).

In any case: robots indistinguishable from humans; self-driving cars; cold fusion; advanced quantum computers; artificial intelligence that can rival the human kind… The list could go on forever. There are so many technological fields in which we talk of a huge breakthrough, some of which have been expected for more than a century, and still… As Hamish McRae quite rightly writes, it is very hard to guess which technology will manage to break through and which will run into an unexpected obstacle. And, not least, whether a given solution will turn out to be economically attractive, ready for practical use and for meeting society's prejudices.

What do you think the next big technological breakthrough will be?

2. Never sit idle

“We do not choose professions that will soon be practiced only by robots. Most of us realize that during our working lives we will have to retrain several times. That is why creating some picture of the future would be useful for people, so they can clarify their ideas and expectations.”

“Just as in 1990 it was impossible to foresee the boom of new professions that occurred in the period up to 2020, so today it is impossible to know in what fields people would want to work in 2050. But we can guess some of the social and educational attitudes that will be in demand by then. They will include some ‘hard,’ or basic, skills such as literacy and numeracy, but also ‘soft’ ones—such as flexibility and empathy toward other human beings. How young people will be taught, encouraged and mentored to develop such qualities is another matter.”

Literacy… really?

“Which professions will artificial intelligence take from us?” Well… the ones we give it. Or the ones it will take for itself? For the past two years we have not stopped asking this question; I ask it of my guests too, and the answers range across a remarkably wide palette. Here you can read more about the trends, and still, it is worth thinking it over before the moment comes when the job market suddenly stops “selling” a given profession.

Will we be freed up with so much time that we will have to start learning to be bored well? Will we arrive at such extreme and hotly contested solutions as universal basic income?

Basic skills such as flexibility and getting along normally with other people will surely remain priceless. And perhaps most important of all is attitude—we live in ever more dynamic times, and that is unlikely to change any time soon.

3. Who could have told you?

“The future development of other kinds of services does not look so clear. A peculiarity of communication services is that nobody knows what service people would want to buy until someone invents it. We did not know we needed Facebook until it was offered to us. The same goes for the whole field of social media. Most of the information services that will dominate the market in the years up to 2050 have not even been created yet.”

“Revolutionary innovations come about either as a result of sudden scientific discoveries, or when several existing technologies are combined and refined to create a new product or service that spreads rapidly around the world.”

Indeed, who could have guessed that we would invent something like social networks, capable of hijacking such a share of our time and attention? Ready to fundamentally change the way we communicate as a species, but also the way we take in information and learn about everything happening around the world…

Lately there has been more and more talk of the successful startups of the future, which could generate attention and profits while being built by a single person helped by artificial intelligence.

The good ideas are “on the table,” the prejudices will not go away, and exciting new ideas are on the horizon. Which direction will they take?

4. Alive, well and educated

“In the future, the most valuable skills will be those of offering services that the whole world wants to buy. It is already clear what some of these services will be. Education and health care stand out in the top two places, because even now the need for both is boundless.”

“In 2050, health care will be of far higher quality and probably cheaper. Not only will we know better what is wrong in a patient's body, but their health will also be monitored in real time. Diagnosis will be automated, and medical intervention will be more precisely targeted for the optimal response to whatever is wrong.”

We often talk about the expected breakthroughs in the world of medicine (for example here and here) on Digital Stories. Many assumed the pandemic would attract huge investment in this field and that big news would quickly follow. Perhaps we still do not notice it, but there are definitely remarkable solutions simmering in the pot of medical innovation that will change all our lives.

And yet… out of all fields, should it really be health care and education that enjoy the most spectacular rise? Isn't Mr. McRae being a little too optimistic? If he turns out to be right, we may well get the chance, in good health and eternal youth, to discuss the topic again in 2050…

5. Learning is still learning

“Over the next thirty years, the boundary between the education industry and the businesses inspired by it will fade more and more. Universities will increasingly resemble business institutions, and businesses will resemble institutions of higher learning. This is already happening, but the change that has begun will gather pace. The only realistic way forward in this field is to use information technology to achieve greater efficiency.”

What now?! Is it worth getting a university education that will be outdated by the time we graduate, because of the next big technological steps? Should we seek narrow specialization, or turn toward what we used to call general knowledge?

One thing is certain: in the age of advanced artificial intelligence, education faces serious challenges. But also huge opportunities, as long as it finds well-grounded and meaningful applications for it.

6. AI. So what?

“Artificial intelligence is a superb tool for analyzing data—much better than humans at this task. But it is useless in many other areas of life. It cannot empty the dishwasher, for example. So artificial intelligence is very useful as long as the sea of data keeps flooding us. It can beat us at chess, but it cannot help us find a cure for cancer. We are still at a very early stage of grasping the capabilities that artificial intelligence possesses.”

We come to the big question. A year and a half has passed since ChatGPT appeared on the horizon to show the general public how far we have come in imitating the human brain. And then… has artificial intelligence really stepped in everywhere? Has it fundamentally changed every area of our lives, or is it simply a matter of more “technological time”?

Are we on the road to the much-talked-about artificial general intelligence? Or are we close to the limit of our current approach to artificial intelligence, and of the data we can use to train it?

You will find meaningful and up-to-date answers on the subject here.

7. Nothing stays hidden

“The use of artificial intelligence raises a number of problems. One of them is the invasion of privacy. To what extent would we want not only our personal data to be analyzed, but also all the data we create in our everyday lives? Another problem is abuse, because it has become clear that artificial intelligence can be abusive just like the natural kind. A third problem: how do we use the more straightforward abilities of artificial intelligence to analyze data and reason logically alongside the more flexible abilities of human intelligence, such as empathy, creativity and imagination?”

“There is no precedent for such a state of affairs. The world has never been a place where almost everything is known about everyone, and where the system raises a flag if any gaps are found about someone. So we face a period of two or three decades in which individual societies will grope around until they find where to draw the line between privacy and publicly available personal information, and how to protect the former while expanding the latter.”

Here are some of the big questions on this topic whose resolution we keep postponing and postponing.

• About the data we so casually leave all around us;

• About the opportunities for manipulation to which we open the doors wide with every new technology;

• About the crime-free future artificial intelligence could lead us to…, which can easily turn into a digital concentration camp;

• About the huge, absolutely necessary changes facing today's democratic systems;

• About the digital inequalities which, by all appearances, keep deepening with the progress of artificial intelligence.

8. Babies made to order

“In the field of biotechnology, surprises can almost certainly be expected. Will rich people in developed countries try to create perfect babies, whatever that means? Or will the aspiration be more general, affecting people in many countries who will want the genes of their offspring manipulated so as to give those babies a better chance of becoming balanced, happy people? These questions sound rather disturbing, but with the development of genetic engineering it will become impossible to ignore them.”

And although in his book the economics journalist focuses precisely on economics and politics, other topics appear in it too, discussed far more rarely but no less important. Topics tied to discoveries that have the power to change us irreversibly as a species. From designer babies through uncontrolled genetic manipulation and artificial wombs to rethinking who we humans are and where we are heading…

9. The battle for truth

“The vast amounts of inaccessible information, along with the growth of social networks, have led people to believe less and less of what they read and watch. Many have started selecting the opinions and points of view that match their own. On top of that, such people also select the news that chimes with those views, making them even more favored. Very alarming is the observation that the more educated a person is, the more inclined they are to seek information confirming their opinion and to avoid information that calls it into question.”

“I hope that one day, when people get used to the abundance of information and to the dangers that social networks hide, the benefits of the wide availability of knowledge will be seen much more clearly. Cults and conspiracy theories will go on sprouting as they always have, but there will be enough common sense to allow humanity to keep walking the path of true knowledge.”

I like Hamish McRae's optimism that we will learn to treat information more carefully and critically. To treat the important topics, the conversation, that way.

Because, I truly believe it, you are not what you eat, but what you read.

Because what this future will look like depends on the very way we discuss it and make sense of it.

(More on the subject here.)

10. Evolution or revolution?

“Technology will continue to develop. In most cases this will happen gradually, but there will come a moment when human knowledge undergoes a radical change, after which everything we have known until then will appear to us in a different perspective. Will this change have anything in common with the way Charles Darwin explained the origin of the human species in his book ‘On the Origin of Species’? Or might it be some technical discovery comparable in importance to the discovery of antibiotics, or—God forbid—something like the atomic bomb? Both are possible, and equally so.”

Musk said recently that in his view, as early as 2025, artificial intelligence will become smarter than any human on the planet, and by 2029 it will surpass all of humanity combined. On the other side, countless skeptics can be quoted with ease.

Surrounded by information noise, and by all the illogic of technological progress we have talked about, it really is hard to judge exactly where the next big change will come from.

Or how. Will we wake up one day in an entirely different world, as happened, for example, after the first nuclear bomb was detonated? Or does change come slowly, imperceptibly, until new technologies are not only capable of replacing the work of people in a given profession but actually do replace them? When homes are no longer built but printed, when artificial intelligence takes on so many new roles…

What do you think the next big change will be? If it has not yet been discussed on Digital Stories, suggest it to me here, and a gift awaits you in return.

Forty-six-year-old Bryan Johnson has already spent more than $4 million to make his body work like an 18-year-old's. He claims it is working. He puts everything into it, going as far as infusing himself with blood plasma from his own son. He believes he is the most measured human being who has ever lived, and that his experiment will change the life of everyone who wants to live long.

In other words, everyone.

Dream or utopia? An obscene waste of money or an idea that could change our evolution? Genius or sheer madness?

“Who wants to live forever?” Freddie Mercury asked in song, before he was taken by AIDS—a disease we understand and treat far more successfully today than we did back then.

And who doesn't? The real question, though, is what we do about it, and Bryan Johnson is an impressive example. A multimillionaire and successful entrepreneur, he has devoted himself to a fascinating experiment whose goal is to drastically extend human life. And his guinea pig is himself.

Don't Die!

That is Bryan's motto. Fine, but the task is far from easy, as anyone born more than 130 years ago can confirm, if you ask them. Here he is in front of us, and you certainly wouldn't put him at 46—at most 45.5. I'm joking; he is undeniably youthful.

As the journalist Charlotte Alter aptly noted in her piece for Time, his body looks 18, while his face looks… like that of someone who paid $4 million to look 18. According to his own data, by almost every physiological marker he matches that age, and by some others he is in the healthiest 1 percent of 18-year-olds.

Isn't time the most precious thing, the only resource we can never get back? It isn't a social construct like money, but pure objectivity. Who is the crazy one: the man who uses his millions to pile up more millions… or the other one, who tries to buy himself time?!

And so methodically and deliberately, too. Yes, perhaps beyond common sense, but “the end justifies the means.” That bit of wisdom is attributed to good old Ignatius of Loyola, whose fanaticism is rather reminiscent of Bryan's. Except that you probably don't know the full version: “If the end is the salvation of the soul, then the end justifies the means.”

Bryan's Life

The salvation of the soul? Bryan has no time for that; his obsession is the body. Every second of it is tracked in every possible way. At the risk of horrifying fans of homeopathy: he takes an average of 111 pills a day.

Some of his solutions sound extremely exotic. He wears a baseball cap that beams healthy red light at his scalp, sleeps every night with a small device strapped to his penis, and every day hands in stool samples for analysis…

But really, what good are all the money and all the next technological leaps if we are still shackled to that maximum lifespan, which falls so far short even of the figures in the Bible? Or take average life expectancy—the COVID pandemic crushed it even here in Bulgaria, where it was appallingly low to begin with.

According to Bryan, every action that speeds up aging—from sleeping less than 8 hours to nibbling cookies late at night—is “an act of violence.”

Oh, Wretched Youth

Blueprint is the name of the project organized by the millionaire, in which he himself plays the lead. His condition is monitored at all times by expensive doctors. Every important vital sign is watched with extreme precision. Meanwhile, another team of scientists has the job of following the latest publications, so as not to miss some tiny discovery that might add a minute or two.

It would be convenient if life were an equation and you could just do the math. Decide to add smoking: minus 3 years; drinking: minus 2; following Bulgarian politics: minus 12… Yes, years ago we in the media fell for such convenient explanations, but they don't work, at least not that directly. And still, every day we face decisions like these, which, alas, not even ChatGPT can turn into exact mathematics.

Many other billionaires—from Bezos to Sam Altman—are putting serious money into this field. And Bulgarian scientists have turned their attention to longevity research, too. So why is Bryan's attempt treated by both the media and the public as something eccentric?
The goal is simple. To make the organs of the body work as they do in an 18-year-old—for now in Bryan, and eventually in everyone. Indefinitely. At the moment, Blueprint rates its boss's skeletal system as that of a 30-year-old and his heart as that of a 37-year-old. According to Johnson, this is already a major breakthrough—a clear system that helps you make the right decisions far better than you could intuitively. It tells you how long to sleep, and you comply. It tells you which lunch dish is the healthiest, and that's that… a fitness coach, only for life itself.

The Early Bird Bleats

He usually gets up before 5 a.m.… which makes you wonder why he wants to live so long.

His bedroom is like that of a monk on Mount Athos—no photos, no books, no TV, no phone charger while he's in there, not even the phone itself! Here he only sleeps, and in his view this is a key factor in turning back the clock. The only things inside are the laser generator that rejuvenates his skin and the aforementioned device that tracks his nocturnal erections. Because, according to his team of scientists, their duration is an accurate indicator of one's current state of health. At the moment Bryan enjoys an average of 2 hours and 12 minutes; his target is the average for an 18-year-old—3.5 hours. Things would get a little awkward in Bulgaria's state outpatient clinics if they introduced this particular diagnostic method.

Once up, the millionaire measures his weight, body mass index, hydration level and body fat. Exactly when he provides the other sample we mentioned, he doesn't say. Then he stands in front of a special lamp that imitates sunlight, to set his body's rhythm. He quickly takes the temperature of his inner ear, and then comes the moment for several dozen dietary supplement pills. Anti-wrinkle cream, a face mask… and he is ready in just an hour, which for many ladies getting ready for a formal dinner would even count as quick.

46 Years Aren't Enough

By 6 he is fresh as a cucumber (only with smoother skin) and ready for work. That is—for the next round of measurements and pills. His freshness is surely helped along by the sinister greenish smoothie called “Green Giant,” with secret, proprietary ingredients—coffee, naturally, is out of the question.

Every day he does an hour-long workout at the gym, with more strenuous exercises three times a week. I don't think there's any point in bothering you with the rest of his daily rituals—they go on in the same spirit, and he shares them copiously on Instagram, as well as in the detailed protocols of all his tests, which he publishes on his website. In the first 5 months alone, 180,000 people signed up for his weekly updates.

When You Shuffle Off This Mortal Coil

Blueprint launched on October 13, 2021, which means that in just 2 years he has already worked wonders. “Blueprint is STEM (science, technology, engineering and mathematics) for health,” Bryan says. “My team and I set out to do what no one had done before: to let the body run itself. I carry out hundreds of measurements of biological processes, allowing my heart, liver, lungs and kidneys to tell me for themselves what they need to be in ideal condition.

My mind—a storytelling creature—is not authorized to go shopping, to browse the pantry, to order pizza on a whim, to eat dessert… in practice, to make decisions. My practical and immediate goal is for the 35 trillion cells that make me who I am to work together in the best possible way for optimal health and youth.”

I Am Young, Yet I Remember No Youth

“Most people believe that death is inevitable,” Bryan says. “We just try to extend the time we have left before we die… But that's how it has been until now. I don't think there has ever been a moment in history when Homo sapiens could say with conviction that death might not be inevitable.”

I mentioned that he had infused himself with plasma prepared from the blood of his own 18-year-old son. This scandalized quite a few of his followers, but he quickly stopped the procedure—because, he says, it turned out to be ineffective.

Bryan has three children, now fairly grown up. Their birth and childhood coincided with the rise of the business that made him rich. In 2007 he founded Braintree, an online payments startup that later became part of PayPal, and Bryan walked away $300 million richer. He says, however, that he was unhappy at the time and fell into a depression that lasted 10 years.

My Old Friend

He put on 50 kilograms of excess weight and was unhappy with life. A devout Mormon in his youth, at some point he left the church and divorced. Today his elder son is a Mormon missionary, his young daughter lives with her mother, and his second son lives with him—it is Talmage who became the donor for his father's cause. The two get along great; the 18-year-old even follows part of the Blueprint diet, sparing himself only the anti-aging therapies for now.

Officially, Bryan has no girlfriend (perhaps so as not to skew the nighttime measurements), but recently his marketing assistant, Kate Tolo, joined the experiment. She is 27, comes from Australia, has experience as a fashion expert, and for a few weeks now has been the first “test subject” meant to check how Blueprint works on a female body.

Bryan believes he is single because he is completely upfront on a first date. “Dinner at 11 a.m., bed at 8:30 p.m. No pillow talk, no small talk, everyone sleeps alone. Sex is scheduled. No vacations in the sun, no meat. You have to donate plasma and, no, you are not my top priority.”

Young and Crazy

Every year he makes important resolutions, he says. “My resolution for 2013: invest in technology companies that make the physical world programmable. 2016: found a mental health company. 2020: create Blueprint to explore the defining question of our time: is death inevitable? To create, and make free for everyone, potentially the most powerful health protocol in history.”

There is a resolution for '23 as well: “Don't die. Let's not die. Let's not kill one another, let's not destroy our biosphere, let's not underestimate the importance of aligning with artificial intelligence.”

Dr. Nir Barzilai, director of the Institute for Aging Research at the Albert Einstein College of Medicine in New York, met Bryan at one of the annual conferences on the subject. “He looked sick. He was pale. I don't know what he's done to his face,” says Dr. Barzilai, adding that he is worried by the idea of having no fat in the body. He adds that combining more than 100 dietary supplements may not be the best idea. If you ask me, he's jealous.

Highlander

How does Bryan himself deal with the haters? “The troll in my head is far nastier than the ones I meet. When I was depressed, my brain kept telling me, ‘Life is hopeless,’ and I had to learn not to listen to it. While people troll me, I play with them. Frankly, it isn't even interesting anymore.”

Bryan has 30 doctors on his team, led by 29-year-old Oliver Zolman. The rest remain in the shadows; so far none of them has appeared in the media. But it is no secret that once Blueprint is perfected, the first eternal youth plans to turn it into a product, a system that will bestow the same eternal youth on mere mortals. It is a fact that not everyone can set aside $4 million for a system of their own. In fact, on the average Bulgarian salary, you would need about 342 years. Assuming, of course, that you don't retire in the meantime.

How much it will actually cost us to secure those years through the system is not yet known.

He promises us that the next version will be free and cheap to follow. Yes, he already sells olive oil with his face on it, but he says profit has never been the goal.

Besides, it isn't clear whether we should trust him before he reaches at least 100 or 200 years. But here we enter questions too philosophical, where artificial intelligence is still better than we are.

122 Years of Solitude

Before we part, let's bring one more character into the plot. You have probably heard of Jeanne Calment, the longest-lived person on the planet (at least until Bryan “beats” her). Born in 1875, she died at 122 years and 164 days. She smoked from the age of 21 to 117 and said she owed her longevity to a diet rich in olive oil, port and lots of chocolate, nearly a kilogram a week. But above all, she pointed to serenity as the main reason for her long life.

She never lost her sense of humor, right up to the last day—when she was already past 120, a journalist told her he hoped to see her again the next year, and she replied: “Why not? You don't look so bad.” “I've only ever had one wrinkle, and I'm sitting on it,” Jeanne also used to say.

Well, Bryan is like that too, at least when it comes to wrinkles. And which of the two will prove more successful at stopping the clock… I'll be glad to discuss together after Bryan's 123rd birthday. Until then, as a popular Bulgarian media personality likes to say: “Stay healthy!”

– How did you end up in bioinformatics?

– I started 20 years ago. I was a first-year computer science student at Sofia University, wondering which direction to take. Around that time the first draft of the sequenced human genome came out, and it was all over the news. I read about it, found it fascinating, and started digging deeper into the connections between molecular genetics and computer science.

The human genome is one big text, a sequence, a string about 3 billion characters long.

If we want to study it, we have to apply computer algorithms—there's no way to do it by hand. The field grabbed me very quickly.

– What exactly are you working on right now?

– Illumina makes almost all the machines used when someone wants their genome sequenced, or for any kind of DNA-related research. My team is part of the company's artificial intelligence department, where we develop methods for interpreting this data. When someone's genome is sequenced, you see the differences—the mutations between it and the reference genome—and you need to figure out what they mean.

On average, each of us has about 4 million mutations. Most of them have no effect whatsoever on our health or appearance.

With the algorithms we develop, we try to find out which ones are the others and how they affect our health.

– What are the applications?

– Very roughly, there are three: predicting genetic risk, diagnostics and pharmaceuticals.

The first is predicting from someone's DNA whether they will develop a particular medical problem. This area is growing enormously; there are models that predict the risk of cardiovascular disease and various types of cancer. There are genes like BRCA-1 and 2 where a mutation gives a woman a more than 50 percent risk of developing breast cancer. If she knows about such a risk, she can take precautions in advance.

The second application is making an accurate diagnosis when there is a problem. There are 6,000 to 7,000 rare genetic diseases, and for only about 1,000 of them do we know which mutation causes them. For most, nobody knows, so the DNA is sequenced, all the mutations are examined and ranked to find the most likely culprit. Right now this is done by specialized genetics experts, and the average success rate of these diagnoses is just 20 to 30 percent.

The third application is pharmaceuticals. The goal is to find new drugs that treat diseases more effectively and with fewer side effects. Large datasets of sequenced genomes are used and matched against information from medical records.

– Today it's affordable to have your genome sequenced. But when does it make sense if there's no medical reason?

– I can speak from personal experience—I've had my own genome sequenced twice. The accuracy of these tests is incredibly high: both times I got exactly the same set of mutations. The detection technologies themselves are precise. The question is

what a person can actually do with that information, and in reality… there isn't much.

If you're relatively healthy, we still don't know enough about how to predict the risks for most medical problems. But that's expected to change quite soon, and we're working actively in this area.

There are websites where you can send your data and get some kind of analysis. But looking at my reports, I wouldn't say there was anything meaningful. One of them, for example, returns a list: this mutation raises your risk of prostate cancer by 0.5 percent, that one lowers it by 1 percent, a long list. But there's nothing meaningful I can do with that information. I showed it to my family doctor. One of the things that came up for me was an elevated risk of iron overload in the body. I asked the doctor to test me. She said there was no indication for it, but agreed, we did it, and the result was normal. After quite a bit of reading, I found out that the mutation I have raises the risk only in the presence of a second mutation, which my genome doesn't have.

– Then again, once you have such data, there are platforms that notify you when new scientific findings appear about a mutation you carry. Perhaps the moment isn't far off when this will happen for more conditions and with far more convincing percentages?

– Yes, this field is still in its infancy; we're only beginning to discover what these reports actually contain. I'm sure my list of mutations includes interesting things, and some that deserve attention. We just don't know yet which ones they are. Artificial intelligence will play a central role in this area.

– Forgive the naive question, but why is it so hard to understand what lies behind each mutation? You get one big text, a string, and lists of people with certain conditions. Shouldn't the patterns be relatively easy to find if there really is such a direct link—say, a mutation that raises the risk of a disease by 80 percent?

– It's hard, first, because these mutations aren't that pronounced. If one is highly lethal, the children who carry it won't be born. Beyond that, you see mutations that show up at an early age, but they're relatively rare. And most occur in people who are relatively healthy and show up later in life, usually after they've already had children.

The second reason is that reading a genome used to be very expensive—the first one, in 2001, cost about $3 billion. Today a person can have it done for about $200. People in my field love to show the graph of Moore's law—transistor density doubling every two years—and next to it they put the cost of DNA sequencing, which falls much faster. Much of the credit goes to the company I work for; the technology has developed very quickly over the last 10 years, and prices are expected to fall further.

Only now does this allow us to sequence the genomes of large numbers of people. At the moment I'm working with a database of half a million people from the United Kingdom, and we have their medical records too.

Until a year ago this wouldn't have been possible. In a database like this you can now establish the link between genes, their mutations and medical problems.

The third reason is that genetics isn't the only thing that determines our health. Health is also the result of environment and lifestyle, combined with the genetic material we carry and the interaction between the two. For some conditions the environment matters much more—if someone falls from too great a height, for example, it makes no difference what genes they have. For some diseases genetics has a big influence; for others the environment matters more. So we need to understand what share of diseases belongs to the first group.

And finally, biology is extremely complex. Our genome is a “book” 3 billion letters long. But it's full of all sorts of things, and the part that codes for proteins is only about 2 to 3 percent. Much more of it is repeating sequences, and there are also retroviruses that got written into it over the course of evolution. It's very hard to understand what in the genome is important and what less so, and how the important elements work inside the cells.

This chemical machine that our bodies are is extraordinarily complex.

– Maybe we simply overestimated the influence of genes and heredity, looking to them to explain so many things in life? At the expense of, say, epigenetics—the way the environment changes our genes. I remember the enthusiasm around the first genome sequencing and the expectation that we'd be able to predict practically every disease.

– Yes, it turned out not to be so easy. Those ideas impressed me back then too, and they're what drew me into the field. It's hard; there are many layers. You mentioned epigenetics—that's yet another layer of information, encoded not in the DNA itself but in its modifications, and it determines how genes are regulated. In most cases this regulation is very strict and rarely changes.

– What are the most interesting developments, the big breakthroughs, you expect in the coming years?

– I think they'll be in pharmaceuticals. It's very hard there too; we thought it would be easier for artificial intelligence to open up that field. I also expect news in the diagnosis of rare diseases and in predicting genetic risk. That's what I expect in my own field, and more broadly, in biotechnology. That area is developing very actively right now. Gene therapies, for example.

– Will the moment for personalized medicine arrive?

– Yes, I expect it will. I think new technologies will merge with current medical practice. This personalized approach will be added, where we'll know the individual characteristics of the person the doctor is treating and what's best specifically for them.

There will be drugs made for a specific person based on their genetics and clinical history.

There are attempts in this direction even now, but I think it will also take time. The current system works on the basis of its historical practices, and they won't disappear overnight.

– There was hope that, because of COVID, a lot of money would flow into medical technology and within just a few years there would be big breakthroughs. I still don't see them. Are there any?

– They're simply hard to achieve. They're possible, but they take a lot of time, studies and research, trial and error. In scientific work, most of the time nothing happens—you try, nothing works, and only very rarely does something succeed. After that, it takes time and money before it turns into a product: a drug, a therapy or a diagnostic test.

These things will come into our lives. The good thing is that an enormous amount of data is being generated right now

– from genetic tests, from medical records; gigantic databases are being assembled, and that allows computational methods to develop. Until recently this wasn't possible. Last year we had that “ChatGPT moment,” when people got goosebumps seeing the impressive chatbot.

Such a moment will come in medicine too. But ChatGPT's success comes from having huge amounts of data, people working on the models, and computing resources. All of these things are happening

in genetics and biotechnology as well, and I think it will be one of the next fields to experience a “ChatGPT moment.”

– Let's hope so! And how do you see the idea of gene manipulation? CRISPR technology offers enormous possibilities; it seems we're on our way to treating more and more diseases this way…

– These technologies offer great opportunities for new therapies. Gene manipulation is already done routinely in research labs. For any larger-scale applications, though, we have to proceed very carefully. The risk has to be limited, and these technologies must be handled conscientiously. There are gene therapies for diseases that have no other adequate treatment, and I think it's right to use them, provided safety measures are taken.

A few years ago there was a scandal in China: a professor had edited human embryos, from which babies were born. He had edited the CCR-5 gene, the receptor that HIV uses to enter human cells. There are people with a natural mutation—around 10 percent in Northern Europe—who are naturally immune to HIV. He had decided to induce the same mutation in babies.

It's not clear why it had to be done; those babies weren't at risk of contracting HIV. It's also unclear whether such mutations might have other effects, and whether the editing technology is precise enough not to cause additional mutations with side effects. Very often

some changes in DNA protect against one disease but predispose you to another.

The case caused a huge scandal, and the professor was arrested. It had a negative impact in the biotechnology and human genetics communities. I, too, believe it was a pointless and unnecessary experiment, with no benefit but with risks. All while turning public opinion against doing experiments.

– When CRISPR appeared, the other worry was that we'd soon have “designer babies.” But that also turned out to be much more complicated.

– Yes, it's harder! There are some companies working in that direction right now. It's a very controversial question whether it makes sense to do it, and also whether it's possible at all.

Many mutations have side effects. For example, in Africa there are populations with stronger immunity to malaria, but it predisposes them to sickle cell anemia. The same goes for many of the traits people would like to optimize.

– Figuratively speaking, we don't know whether making a child blue-eyed might raise their risk of cardiovascular disease.

– Yes, you have to tread very carefully, and at least for now I see no point in doing it. Our goal is rather, when there are sick children, to look for a way to cure them.

– Do you think it's worth guarding our genome data, not showing it or sharing it?

– This is another area where people have strong opinions. It's good to protect your personal information—we don't hand out our national ID numbers to everyone. My view is that right now there can't really be any danger from someone learning your genome.

There are fears that insurance companies might refuse to insure you, but for now they're fairly hypothetical. In most places there are laws regulating their obligations. Besides, they already know quite a lot about people, and this additional information doesn't give them all that much when it comes to assessing risk.

Not long ago there was a case where the police here had been investigating a murder for 20 years. They had a sample from the crime scene, had done a DNA analysis and compared it with the database of one of the sites where you can search for relatives by DNA. The sample revealed family connections, they saw where those people lived, and they managed to track down who had committed the murder!

That also sparked debate: people send in their data to look for relatives, and the police can come along and run such searches. My personal view is that my relatives and my children had best stay on the right side of the law.

Yes, some unexpected applications may emerge—the fact that you took a test could affect others in some indirect way.

– It's easy to let your imagination run wild. We're working in science-fiction categories, because that's where technological progress is taking us.

Is there an achievement you and your team dream of reaching?

– I'd like us to make genetic predictions and diagnostics available to as many people as possible, even those who have no way of seeing a doctor or a genetic counselor. For these technologies to be accessible to everyone, so that everyone can benefit from them. I'd be extremely happy if we managed to cure some disease—it doesn't matter which one.

– I wholeheartedly hope it happens soon! Thank you for the fascinating conversation.

– You recently returned from the world forum of futurologists in Dubai. What impressed you the most?

– One thing was the meeting with the astronauts of Expedition 69, who returned from the International Space Station on September 23—two Russians, four Americans and the first astronaut from the United Arab Emirates.

I expected them to talk about scientific experiments—they had operated on a blood vessel, tested whether heart surgery or meniscus surgery could be performed in orbit, which matters for the projects to colonize Mars and the Moon. But what they shared was deeply human—the psychological threshold of being so far from Earth. The fact that it turns into a small, beautiful blue dot makes them rethink a great many things. Until they saw the atmosphere as something very fine and delicate, they had never realized that this layer, which shields our lives from solar radiation, is so fragile.

The other key message was how dependent they are on one another. They wanted to show that when humanity faces a truly important global question that concerns everyone—in this case, the success of the space mission—geopolitical and strategic stories don’t matter at all. Both the Russians and the Americans said:

we want to give humanity the formula for understanding, the model for success, for cooperation,

up there we are interdependent and we truly are like brothers.

– Alas, we can’t all go up there to see it for ourselves, and technology helps us forget it more and more.

– The other interesting encounter was with a well-known technological absolutist, optimist and influencer—Whurley. He handed out booklets made entirely by artificial intelligence, with very beautiful illustrations and text. He asked a series of questions along the lines of: why does world hunger exist when a third of all food is thrown away? Why can’t we cope with climate change and environmental pollution? Why are diseases that had disappeared coming back?

He expected us to supply the answer; he built his presentation on that logic, to show us that the elephant is in the room and we don’t see it. The answer was that there are about 8 billion of us, and only 0.1 percent are scientists—people who actually do science. While we complicate our lives with the technological revolution, we have extremely complex problems that keep reproducing themselves.

His thesis was that the only way to close this deficit fast is to use artificial intelligence, and the more advanced the better. At the end he revealed the secret: the brochure had been created by his 6-year-old son in 30 minutes. He said that

children already have a very good intuition for working with these technologies.

They aren’t biased, they don’t expect complexity and impossibility; they just use their imagination and creativity, and they handle it very well.

I recently came across an article saying that America has only now set a date for landing on the Moon, because it turned out that part of the calculations, part of the technology, was lost from the days when mathematicians computed everything by hand.

– There’s that famous photo of Margaret Hamilton, who led the team of programmers, standing next to all the code they wrote—and the stack of paper is as tall as she is!

– Exactly! One hypothesis is that NASA hasn’t managed to send a new mission not only because it’s expensive, but because part of the technology has been lost and they can’t reconstruct it. I asked him about it in that context. We use artificial intelligence, it is becoming ever more perfect, it is already on the border between narrow and general, large language models produce flawless results when given a precise task.

There will certainly be a boom in scientific discoveries; I see it in the finding of new galaxies, in the detection of cancers. AI processes big data and calculates incredible things.

We have enormous opportunities, but we may fall into the trap of the easy road.

Just as the knowledge behind Apollo was lost. If, because of ChatGPT and the other models, programmers themselves stop developing mathematical code and that knowledge is lost after a generation or two, what happens? What if we walk into this trap, simply turning everything into tools and replacing mathematics with a game of symbols?

Whurley chose not to answer me.

People of this type, with this mindset, are very useful. They want to go all the way, and they have their place. But the threat is real—like in the films where a solar flare wipes out electricity and the internet, and people no longer have the analog thinking or the instinct for where to start, how to rebuild that knowledge.

The people of the future, completely dependent on the digital, may have to rediscover everything in some primitive way. There has to be a plan B and some guardians of the analog. In time we may simply have to take the long road.

– Yes, but who could those guardians be? With artificial intelligence we look for regulation, but states are weaker than OpenAI, than Meta. Even alliances are weak: if the European Union imposes stricter limits, everyone will move to China. The only form of resistance I can imagine, the only chance for regulation, is pressure from society.

– Yes, society could be a good corrective, as it has been on other global issues, like nuclear weapons. I believe that

for artificial intelligence some kind of global consensus and regulation has to be reached, just as with nuclear weapons.

Even if, again as with nuclear weapons, it is used for mutual deterrence, that is better than having no consensus at all. Otherwise, on the principle of tax havens and offshore zones, companies can move to China, for example. Recently a small company, in partnership with NVidia, bought a barge and fitted it with 10,000 powerful processors so they could build artificial intelligence in international waters, beyond the reach of any regulation. They said they would push to become the first AI nation! But in my view this is more likely to make us rethink maritime law, ancient as it is, than to establish new principles.

If humanity doesn’t reach that consensus, we will go through great chaos. It is already creating different jurisdictions—the EU has banned facial recognition, with small exceptions, while in China, India and America it is entirely permitted. The same goes for the analysis of biometric data.

I think the cases that arise will force us to get there, but it will be very hard. The companies themselves don’t want regulation because it holds them back, but on the other hand their leaders fear they could be held responsible in the event of a serious incident. That’s why Sam Altman spent the whole summer traveling and meeting political and economic leaders. One hypothesis is that he was fired because of Q*—a new-generation multimodal artificial intelligence that had bypassed certain measures of control, security and restraint.

– So we are left guessing and relying on rumors about something that may determine our future. Meanwhile Altman is known for having a big bunker, stocked with everything imaginable, so he can survive a cataclysm. But how did we end up with a system in which what happens depends on Musk, on Bezos, on Altman? We’re supposed to be an advanced civilization, yet we’re slipping back into a feudal society—important decisions are made by individuals who consider themselves chosen by God, though no one has delegated such responsibilities to them.

– They all have this kind of messianism. Musk, too, showed great concern, but he did it for commercial and marketing purposes, because he had fallen behind in artificial intelligence. He probably wanted to catch up by calling for a moratorium; the goal is hardly that noble.

These people are the faces of the projects, but behind them stand huge teams, multinational corporations and shareholders who care about profit.

It doesn’t depend on them alone; they embody certain expectations. But the whole situation, for a long time now—since Covid, since before GPT-3—has been rather reminiscent of the film Don’t Look Up. We face problems at different levels, of different kinds, that we can’t solve, and we stand frozen, like a deer in the headlights.

It really is strange that we don’t try by every means to solve the environmental and climate problems.

Even after the worst cataclysm, Earth would offer far better conditions for life than Mars or the Moon.

We still have much better chances here, even if we have to create an artificial atmosphere.

It is also alarming that these people think apocalyptically and look for escape routes, which breeds a lot of conspiracy theories. People start to think that if these billionaires, opinion leaders and trendsetters choose such measures, something is probably going to happen. But they are eccentrics too, also limited by their own irrationality. I don’t believe they possess any hidden knowledge.

The problem is that the political person has disappeared; that figure is in some kind of crisis. This even affects society’s ability to hold a dialogue through the political person, in the collective sense—politician, leader, party representative. It is a consequence of the crisis of ideologies, and it disrupts the dialogue within society and the possibility that anyone can represent it.

We live in hybrid times, a product of social media, which struck at the classic authorities and put influencers, bloggers and experts in their place, rather than scientists.

We have to work in this direction—restoring, reinventing democracy,

so that there are clearly defined actors. They should make clear decisions and be held accountable, because tech leaders are under no obligation to be. We see that nation-states are powerless. That’s why there must be global mechanisms, an institution resembling a global government, only for truly essential issues.

– The UN, only one that works… And we arrive at a moment when we live in incredibly dynamic times, yet America is choosing a president between two men pushing 90. And most major countries are led by people over 70.

– Everything has become very fluid, because we live in a state of constant change.

It is so constant and so frequent that we don’t even need to think about the future; we live with the feeling that the future is now,

that everything is going faster and faster. That the future is far poorer in metaphors and meaning than it ever was.

In such turbulent times, instead of adapting to rapid change, of being like chameleons, people harden and seek conservatism, some kind of fortress. That’s why they choose unfit, elderly leaders—because in the past old age was a guarantee of wisdom.

– I see that conservatism in the comments on my articles too—that there’s a plan to wipe us out and artificial intelligence is just the next step, while according to others nothing has happened in the world of AI and it’s all marketing.

In my view, this reboot of the democratic process, of authorities, can’t happen without some form of media. They are the ones who can validate qualities, serve as a platform for discussion, something that can tame this fluidity. I keep waiting for new media to appear, but they still aren’t here.

– Yesterday I saw a media outlet whose content is generated entirely by artificial intelligence. The presenters are animated figures, but they already have facial expressions and a sense of humor.

Artificial intelligence generates the context for the reports, it also profiles the users and broadcasts news according to their preferences.

This really is the trend Netflix started, toward excessive personalization. For me it is even more dangerous, because it fragments things further and blurs the sense of community. It is what the German sociologist Durkheim called “anomie”—the disintegration of communities. We shut ourselves into micro-communities, and that is a problem. Another problem is how people can resocialize and learn to reach consensus. For now the new media work toward personalization, individualization. Collaboration platforms exist too, but they are voluntary and require initiative. It will be very interesting to see how we deal with this trend.

– ChatGPT has been with us for a year now, and even in the IT community many people say it’s an expensive parrot, that it has reached its limit. That an AI winter is coming, because every field goes down that road. Could they turn out to be right? That we have overestimated what is happening?

– I have never thought so. First, we still

haven’t experienced the multimodal models, and not because they don’t exist, but because the big companies don’t know how to monetize them.

They are looking for a profitable, efficient business model, because these models are very expensive. For a long time ChatGPT brought OpenAI losses, and the company wouldn’t have survived if it weren’t for Microsoft’s 10-billion subsidy.

The paid version of ChatGPT changed that a little; it has around 200 million subscribers, but it is still unclear whether the model is sustainable. Google offers something different: they split Gemini into three models—Nano, Pro and Ultra. Nano is a model we’ll use on our phones and personalize with our own data. Pro will be like GPT-4, and Ultra will have truly exceptional capabilities. So

humanity has not yet fully felt the real effect of what has already been achieved technologically.

The second issue lies in ourselves. We are very conservative, and we are starting to build adaptive responses. Some deny it, others attribute human characteristics to it. Still others say they are taming it, but in fact artificial intelligence is taming us. Even friends of mine believe it is conscious, that it understands them, that it changes its behavior every day; they assign it human attributes. But the fact that we communicate with it as we would with an animal or another person is a process of getting to know it, of overestimating or underestimating the situation. We have no real assessment!

And third—

the statistics on how many people have lost their jobs haven’t come out yet. They will, and then there will be a sobering up,

because there are quite a few. In America, I think 70-80 percent of copywriters are no longer doing that work, and the same will turn out to be true for accountants and legal analysts.

Once these 3 elements sink in, there will be a new attitude. The factors that could lead to an AI winter are falling away one after another. Which is frightening, because at times we humans resemble monkeys playing with fire.

– And Moore’s law still reigns. We reach the limit of one technology and somehow the next one appears, letting us carry on exponentially. Meanwhile the great divide the tech leaders we mentioned still argue over is whether our salvation lies in separating ourselves from technology or merging with it.

– Those are the two doctrines: if you can’t beat them, join them. Or stop them before they destroy you. Merging is, for me, a very interesting phenomenon. I have yet to meet a neuroscientist who can build a scenario of how this communication would work. We communicate through a kind of subject-object opposition, through the eyes, the most natural extension of the brain. When it happens directly, how do we limit our thoughts and our will? How do we know that something is ours, whether it is authentic or not?

Are we all capable of doing it? On the other hand, we couldn’t stop it, because it will give us many solutions. Perhaps

the winning strategy is to buy time, time in which to make up for our cognitive abilities and gaps,

to learn, to understand it and to decide stretch by stretch.

For now, in my view, there is no right strategy. But the time for a pause has already come. So that people can make sense of what has happened, see the effects on the labor market. This will change economic systems! So they can see their own place and get to know the full functionality.

But of course that won’t be achieved, simply because there is no common sense. There is no shared understanding.

As Geoffrey Hinton said: “The aliens landed in my backyard, but they spoke such good English that nobody realized they were aliens.”

– We spoke exactly a year and a half ago, and you said that within 5 years artificial intelligence combined with robotics would change every area of our lives. How does that forecast look today?

– Now it is 100 percent certain.

I think there are 2-3 years left, and that depends on how prepared we are, not on what the technologies themselves can do. If you can think of a field that you believe won’t be heavily affected by artificial intelligence, challenge me, so I can prove you wrong.

– I couldn’t. I am in touch with two professions, and through them with countless others, and I can’t think of such a field. I already see every day how this progress makes the difference, and I wonder whether it is wiser right now to learn how to use today’s technologies, or whether there’s no point, because they change so fast and it makes more sense to develop flexibility.

– We have to learn both. In my view there’s no point in going too deep; the technology is changeable. We have to be flexible, but here again

we fall into that trap of shortcuts, of everything on the surface.

Until we reach the point where we use something we don’t understand. To me that is quite dangerous.

I attended a lecture on the impact of artificial intelligence on medicine. I was very struck by a gynecologist who said that people don’t even fully and comprehensively understand the IVF procedure—it has worked for a long time, but it is a bit of a gamble. As if we have experience, and yet…

– …and yet it may turn out that we don’t know the process well enough. As Anton Donchev said 10 years ago, we carry a phone in our pocket but we don’t know what it may bring us. Whether it might be killing us slowly and imperceptibly. In a sense, that is exactly how it turned out.

– Children are very sensible. Lately I’ve been visiting schools, and they ask me remarkable questions. One girl asked me: “Fine, we’ll reach the limit of our ability to adapt and we’ll simply switch off. What comes then?”

Mental health is already the most important issue, and we can no longer compete, no longer adapt.

We are linear, while technology is exponential. So what do we do? How do we stop this technology?

– We open TikTok and look for a dopamine escape.

– But that makes you unfit.

– So what? The system no longer has much need for you to be fit…

– Yes, capitalism needed people—working and consuming—and that’s why it provided health, education and social systems. Now it has no such need. But

we can’t simply look at people as biomass, unless artificial intelligence decides to.

All the more so since we are opening a little door for it to do just that, by building organoids into neural networks. Here we are already heading toward the bad scenarios.

– The holidays are just over, the new year has arrived—let’s end by looking at the good scenarios. What news would you be glad to hear in the coming year?

– The discovery of some fundamental drug for fighting cancer; artificial intelligence could do that.

There is a hypothesis that

all human languages share a common root—that the myth of Babel may turn out to be true.

Artificial intelligence could prove it! It could give us a better understanding of our origin as a species, or of the origin of life on Earth altogether. Those very important scientific questions around which we have built beliefs, religions, ideologies and social systems. It could shake them, and it could also make us better, more humane…

Information technology has always tried to imitate nature's most perfect model: the human brain. And now it is on its way to doing so more successfully than ever. To build a computer that runs on living human brain cells!

What happens if we bring together the best of both worlds? The biological, with its evolutionary efficiency and its instinctive, creative imperfection, and the technological, with its ability to derive patterns and build on them?

Biocomputers look like the logical future, and it is no accident that many of the people sketching tomorrow have turned their eyes in this direction. Serious scientific breakthroughs and successful startups in recent years suggest that the next big technological leap may well be coming from here. These are the arguments.

Brainwashed

What is a “computer”? The word is new and modern, right? In fact, it was first used in… 1613, when Shakespeare was at the height of his fame, and centuries would pass before we reached the “brainchild” of John Atanasoff, the Bulgarian-American physicist who built the first electronic digital computer. It comes from the Latin for “to reckon,” and the poet Richard Brathwaite used it for people who could solve mathematical problems faster than everyone else.

Its new meaning appeared shortly before the end of the 20th century—“a machine that calculates.” And today we have computers everywhere: in the phone in our pocket, in our watch, in the machine that charges our fare on the tram and the one that counts the ballots (at least in the civilized world).

Over the last few decades we lived through the boom of silicon-chip computers. They developed astonishingly, never pausing on their climb up Moore's law. They kept multiplying their capabilities, their computing power kept growing exponentially, regardless of wars, epidemics and financial crises.

And yet there are plenty of signs that this kind of technology is close to the limit of what it can do. And as Ray Kurzweil says, when a technology reaches its limit, the next one naturally emerges to take up the baton. Perhaps it is time to turn our gaze back… to nature?!

Sense and Sensibility

Do you know the storage capacity of your own brain? At least 2,500 terabytes of data, according to calculations by scientists at Johns Hopkins University!

And with neurons of minimal size, we can process that data astonishingly fast and efficiently. We have before our eyes (or rather behind them) a perfect information-processing machine (whether we use it to make the world a better place or to squabble on Facebook).

Artificial intelligence. Despite the enormous boom in this field, the brain remains the most efficient data-processing structure in the universe. And perhaps it is time to turn our attention precisely to its capabilities. To the idea of turning living cells into computers, of creating an invention capable of “thinking,” of trying to imitate the ideal example…

Chips made of living cells. It sounds like science fiction and, at the same time, so logical!

I Think, Therefore I Compute

But how do we do it? Scientists have quite a few ideas.

One option is to try to imitate the way our brain works; the other is to try to solve the problems it usually solves. These are the strong and the weak approaches to developing artificial intelligence, which Prof. Preslav Nakov explained in detail and in plain language.

So the idea is to imitate the brain, but how does that work in practice? How do we create some tiny unit of “brain” that we can then build on? With chips it is relatively clear: we always come down to binary code—ones or zeros. Here it is not, which is why, in their first attempts to create something similar but biological, scientists split along three paths.

The biochemical approach tries to do it by somehow feeding in the input and setting the computation in motion so that, in the end, it produces a new substance that tells us whether the result is a zero or a one. The biomechanical approach tries to achieve the same thing by analyzing the shapes of the molecule or group of molecules that come out as a result. Bioelectronic computers come closest in concept to the devices we know, relying on detecting changes in electrical conductivity—just as happens in the silicon world.

Well-Oiled Brains

You may have heard of quantum computers. In recent years the field has developed at breakneck speed, and it turned out that to advance in a world where, besides ones and zeros, there is also something in between, we have to change our worldview and our approach entirely.

Well, it makes sense for the same thing to happen with biocomputers. There are many different approaches, and we most likely won't get by without an entirely new paradigm. Then again, perhaps the knowledge we already have will come in handy?

Are there other approaches? There are, and as many as the imagination of science fiction writers can reach (or at least used to reach)—an imagination that today seems to have been taken over by scientists. In 2021, for example, a team led by the biophysicist Sangram Bagh managed to train the bacterium E. coli to solve a small puzzle made of 2 by 2 pieces.

Bits and Neurons

Have we limited ourselves to silicon, missing many different ways of building computing machines that are more natural?

Much of the hope of turning biological cells into the building blocks of computing machines rests on CRISPR technology. The much-hyped method for editing DNA (which will certainly get a more detailed look in a future Digital Story) has already shown that cells can be genetically engineered to perform computations, producing specific proteins as the output of the manipulation.

Brainy

Nor is recent progress in this field science fiction. In March, scientists at Johns Hopkins University showed for the first time how close we are to biological computers. Using cultures derived from human brain cells, they managed to “grow” cell cultures capable of computing.

To do this, they create organoids—structures that cannot perform all the functions of a real biological organ but are able to carry out a particular task. They are biological tissues grown in laboratories, most often from stem cells, and in this case the goal is to mimic brain cells. According to the scientists, once the technology matures, organoids could be even more efficient than today's computer processors. And they will be especially valuable in precisely the field that is booming so much today—artificial intelligence.

In this context, even the term itself somehow finds a more fitting embodiment…

Too Clever by Half

“We are currently reaching the physical limits of silicon computers, because we cannot pack more transistors into a tiny chip,” says Thomas Hartung, one of the scientists on the team. “The human brain is extraordinarily efficient at processing information, at learning. It is very tempting to harness and model its abilities so that we have a system that works faster and more efficiently than today's computers.”

“Organoid intelligence”—OI instead of AI, the scientists propose.

Organoids respond to chemical and electrical stimuli and can perform elementary computations. Earlier projects of this kind had developed these new computing units to the point where they could play ping-pong. Perhaps it is no coincidence that this pastime is so popular among programmers, too…

How small are they? Tiny for now, only 4 millimeters long, barely a trillionth the size of a human brain… but if their abilities are comparable, that makes 800 megabytes of memory!

The Little Brain

Of course, for now it is all mostly in the realm of dreams. As the researchers themselves say, they are lucky to be working in a field of science that has yet to lay its real foundations. If today we have only 50,000 cells in such an organoid, according to Prof. Hartung we need at least 10 million to reach the goal.

The best way to feed in input and read out output data is still being sought—so far we have only hints of something resembling electronic systems.

But what if we succeed? What if organoids really do turn out to be capable of solving problems, and of working together? Besides a new form of computer and a new paradigm in artificial intelligence research, we will learn far more about how our own brains work. And all of this may also help in successfully treating a number of neurological diseases whose mechanisms we still do not understand well enough.

A Sea of Wits

The first organoids were created in 2010 by Japanese scientists studying stem cells. It was a major breakthrough, because for the first time we had not just the living cells we need but also a structure in which they come together and interact.

“It is clear that we are still at the very beginning,” says Prof. Hartung. “But leading scientists in large teams are already working in this direction. We believe we will develop a technology that will underpin a new era of fast, powerful and efficient biocomputers.”

“While silicon computers are certainly better with numbers, the brain is better at learning,” says Hartung. “For example, AlphaGo—the artificial intelligence that was the first to beat a human at the ancient Japanese game of Go—was trained on data from 160,000 games. A person would have to play five hours a day for more than 175 years to ‘collect’ that many games.

The brain also has an incredible capacity for storing information. We are reaching the physical limits of silicon computers because we cannot fit more transistors into a tiny chip. The brain, meanwhile, works in a completely different way. It has about 100 billion neurons connected by more than 10¹⁵ synapses. That is an enormous difference in capability compared with our current technology.”

Natural Intelligence

The idea, of course, is not new. As long as 20 years ago, rat neurons grown in a lab were connected to a system that let them control a robot. The University of Georgia project drew plenty of attention… and then nothing more was heard of it. Will something similar happen here?

And what if we go further and… you have your own computer, built specifically from your own brain cells? What if we learn to extract stem cells from each individual and then build a biocomputer from them?

And in imitating the brain, might we not end up imitating feelings as well? And common sense, judgment…? The very thing that makes us human and that, so far, is beyond the reach of even our most advanced technologies?

Dreams are free. In the world of technology, where everything moves so fast, it is worth looking a step ahead. And while algorithms still make mistakes and we have not yet found a good way to imitate the brain… perhaps it is worth keeping our own in shape. And using it as intended, with or without the new technologies.

Left or right? Up!

He believed that when 2030 came, he would wake from the ice to celebrate his 100th birthday. He was convinced that by then we would have reached the heavens and settled other planets. That we would have put our petty squabbles behind us and, lifted on the wings of technology, would be marching onward in human evolution.

Was FM-2030 right? Could the sharp-shooting basketball player still surprise us with a three-pointer of a prediction?

If so, in just seven years we will be able to discuss the details with the man himself. If he really is revived, the forgotten creator of transhumanism, who picked a name like a radio station's, will surely have a lot to tell us… If not, he will become just another dreamer who overestimated humanity and ran ahead of his time.

Fereidoun and the Magic Lamp

It's 2023, and many people write that it feels like the '90s. There is some truth to that: we keep splitting along yet another fault line of the day's outrage, as a nation and as a civilization. Locked inside our bubbles, we find it ever easier, and ever fiercer, to draw the next dividing line through a monument, a currency or a vaccine.

Could the world have been different? No wars, all of us discussing progress in space, huge breakthroughs in medicine, society's agenda devoted to how we use technology and how we grow as individuals, as persons, as a species…

That is how today's hero posed the big question half a century ago. Born Fereidoun M. Esfandiary, a name straight out of One Thousand and One Nights, he went down in history under his fourth and final name, one that would suit an heir of Musk better: FM-2030.

Transhumanism: the strand of futurism that believes it is time for humans to carry their evolution further. That technological progress is here not only to help us fight over Facebook and nuclear bombs, but also to let us touch new worlds. To fly between planets, not as part of state policy or propaganda, but as the natural, evolutionary development of human beings who create the next steps of their own evolution…

Check with a Pawn

What kind of name is FM-2030? The first part is the initials of his birth name (and more besides); the second is the year in which he believed he would be woken from the ice where his (officially) dead body ended up.

But long before reaching that moment, Fereidoun was born in 1930 in Brussels, into a family of Iranian diplomats. His life set off on a cosmopolitan course, which surely shaped his later views. By the time he turned 11, he had already lived in 17 countries. He spent a good deal of time in India; they say he spoke English with an accent all his life.

He went to primary schools in England and Iran and graduated from a Jesuit college in Jerusalem. At 18 he was already fluent in four foreign languages: English, Hebrew, French and Arabic.

He began his studies at Berkeley and finished them at the University of California. He coped well with his studies, but his great passion as a kid was sport. It took him to the first Olympic Games after World War II. At just 18, he was part of Iran's national basketball team. According to some, he also competed in Olympic wrestling, but on this point the archives contradict each other.

Toward a Radiant Future

The Persian team never made it out of the group stage, and that turned out to be the end of the futurist's professional sporting career.

At the time, his country was the arena of fierce battles between rival factions, backed by the states that had just plunged into the Cold War. One more clue as to why Fereidoun would become such a cosmopolitan figure, loathing both the limits of states and civilizations and war itself.

Done with sport, he turned to philosophy. Little by little he established himself as a scholar, teaching at universities in New York, Los Angeles and Florida. He also ventured into the thickets of fiction, publishing three novels that became quite popular and earned him a decent income.

In the '50s he worked for the UN, following the diplomatic path his parents had trodden before him. Thanks to his wide-ranging knowledge, from 1952 he sat on the commission tasked with resolving the Palestinian question.

In 1957 the New York Times ran an interview with him on mental illness in Asia and Africa. He described himself as “an Iranian now living in the United States” and “a freelance writer specializing in the study of social problems in underdeveloped societies.” Oh, how quickly that description was about to change…

FM+

To this day the Palestinian question remains unresolved, and so does the big question to which he devoted his life: our future as a species. Which brings us to the late '70s, when Fereidoun became world-famous for his predictions and his worldview.

He predicted the imminent arrival of in vitro technology, something that still looked like science fiction. He described a future in which conferences and events would be held over a network, with no need for people to be in the same place. He talked about the coming of remote shopping and telemedicine.

The peak of his fame came in 1989, when he published his best-known book, Are You a Transhumanist?: Monitoring and Stimulating Your Personal Rate of Growth in a Rapidly Changing World.

By then he had long ceased to be Fereidoun; FM-2030 had taken the stage as early as 1972.

He officially changed his passport in 1988, because “conventional names carry too much cultural baggage, such as nationality, religion and social background,” and in his view they no longer suited the present day. He said the letters were not necessarily tied to his initials but also stood for “Future Man,” “Future Modular” and “Future Marvel.”

Rather modest, wouldn't you say? A futurist Chuck Norris…

Play the video

As Simple and Logical as That

“I am not the person I was ten years ago, and I certainly won't be in 20 years. The name reflects my conviction that the years around 2030 will be a magical time. We will no longer age, and everyone will have the chance to live forever. 2030 is a dream and a goal.”

And really, Shakespeare notwithstanding, isn't a name very often what defines us? What places us in context, makes us part of our surroundings or outsiders to them?

Of course, FM was above all a provocateur; at the root of his ideas lay the obvious utopia of a world in which technology has developed along the most optimistic scenario. That “technological progress will allow people to become synthetic, post-biological organisms with eternal life.”

Fu-Turist

However much we talk about transhumanism with fear, as a modernized version of eugenics, in the 20th century especially it was an optimistic movement. One that, among other things, turned out to be right in quite a few directions. Yes, by the strict rules of biology we humans are still the same species as those of millennia ago… and yet the change in our daily lives, and through it in everything else, is undeniable.

The dramatically longer human lifespan, advanced medicine, the incredible leap in communications and in how we store and manage our data. Even spaceflight, however much its achievements today lack the magical aura of the '60s.

So, although we belong to the same biological species, we are already different. Because of the way we get our information, because of the way events unfold. Because of speed. Because of memory. Because of our inability to concentrate…

Then shouldn't we pay attention to forecasting, especially when it comes from someone with a serious résumé who managed to predict real discoveries and phenomena in so many fields?

Icy Silence

It's a fact that in many places the former Fereidoun misses the mark. He writes, for instance, that “in 2010 the world will reach a new stage in its history. The family will have given way to universal life. People will come together and part according to their needs, free of kinship and possessions. Life expectancy will be infinite, and disease practically eliminated. Death will be rare, accidental and not forever….”

Well, death is still here, what with pandemics and wars in the heart of the supposedly most civilized world… clearly the interesting part lies not in the extremes but, as usual, in the nuances.

“Genetic engineering to enhance the brain. Implants for a direct brain interface. Implants for direct monitoring of all bodily functions. By 2010 the human brain should already be a supercomputer, independent of the animal body, which can be freely replaced…,” the futurist sketches. He obviously got the year wrong, but as for everything else, isn't it really just around the corner?

He also says: “No civilization of the past was great. All were primitive and persecuting, built on mass submission and mass murder.” It was he who said that “there are no illegal immigrants, only obsolete borders.”

And I wonder… have his words lost all meaning for our supposedly advanced civilizations today?

Nostalgia for the Future

He was a vegetarian all his life, saying he couldn't eat anything that had had a mother.

He defined his views not as left or right but as “up”: toward progress, as opposed to the quick fixes of the day within what he considered an outdated framework. He published three manifestos, the best known being that of the “Upwingers” (by analogy with left-wingers and right-wingers) from 1973. That, he believed, was our important battle: progress against the retrograde, advancement against stagnation, flight to other worlds against staying here on Earth.

In his view it was time to abandon all the ideologies we had used so far, because they were unfit for the new age: communism as well as capitalism. Nationalism, totalitarianism, nihilism. The moment had come to keep only two of them: optimism and universalism.

Re-Contra-Utopia

“We need to develop a bold new philosophy of the future,” says FM. “A hopeful outlook that will encourage people to want to face the future. To want to plan it. I am an optimist, and what I have to share runs against all the pessimism around us.”

When asked about his nationality or his age, he wouldn't answer, because those questions were irrelevant and he was a “global person.” “I am a 21st-century person who happened to be born in the 20th. I have a deep nostalgia for the future.” Oh, if only he had guessed that, with almost a quarter of this century gone, we would not be all that far along, at least when it comes to civilizational choices…

As his rich photo archive shows, in his later years he lived quite well, traveling on yachts and touring the world's resorts. And he took photos, and more photos, including a sizable collection of erotic shots. Although all his life he preached that the idea of the family was obsolete, from 1960 until his death he remained “in friendship” with Flora Schnall, a lawyer and Harvard lecturer.

Death Is a Lonely Business

What's more interesting isn't even how strongly he believed in such an idea in times when not even the internet had been invented. It's that he held on to it afterward, right up to the end of the millennium; optimism never left him. But life did… at least temporarily.

In the year 2000, FM-2030 died and became one of the first people to be deep-frozen in the hope of one day being woken by future humans who have developed technology advanced enough not only to thaw him out but also to cure him of all disease.

Of course, all of this becomes even more interesting in the realm of faith. Because the hero with the alternative name built his ideas on atheism and distrust of all ideologies. Yet he set against them another faith, in technology. That it really would develop so far as to pull us forward as a species… or the other way around?

And then, here is a movement that denies reincarnation… yet believes that one day it will prove itself right precisely through a resurrection?!

According to FM-2030, the human lifespan would become unlimited thanks to the artificial organs we would be able to create. Shortly before his death, he described the pancreas as a “stupid, dumb, wretched organ.”

Well, it was deadly cancer of that very “wretched” organ that took him. And so he became the first person not merely frozen but cryonically preserved, placed at temperatures so low that flesh comes to resemble glass.

Guests from the Future

Even for his time he was too extreme; The New York Times described his predictions as a “Santa Claus machine.” Today, too, his words sound rather naive, given an optimism that time has not borne out. And yet it is astonishing how accurate he turned out to be about the directions he foresaw: the internet and genetic modification, bionics and 3D printing, online shopping and remote meetings.

So was he a dreamer, a visionary or a naïf? Sometimes a person can be all three at once. Look at Musk, who was supposedly so driven toward Mars, and today is looking for a spectacular way to fight (or pretend to fight) with his little buddies.

“I will be so happy when I come back,” he said in an interview shortly before he passed away. 2030 is close. Even in transhumanism, blessed are the believers. And the incurable optimists…

Did Fereidoun have grounds for this prediction? We only have to wait seven more years to find out. Will we harness ourselves to our progress as a species, will we defeat death? Let's hope he turns out to be right after all…

Special thanks to Mario Mishev for helping create this Digital Story!

Some technologies that can save lives are already here, and we simply don’t use them. Not even to help unborn babies come into the world without suffering, without complications that may stay with them for the rest of their lives. To save them.

These days, fortunately, we talk a lot more about providing incubators and equipment to save the littlest ones in their hardest moments. But are we doing everything we can to prevent such situations, to make them rarer?

Not according to our guest today—and he knows what he’s talking about.

“There are so many ways to help unborn babies, I wish they were talked about much more!” says Assoc. Prof. Petar Ignatov, an obstetrician-gynecologist. Besides his wealth of everyday experience, he is the creator of some impressive innovations. The latest of them could drastically improve how successfully doctors use one of the most important diagnostic methods. What’s more, it has the potential to help diagnose and save a huge number of unborn kids.

Can there be anything more important than taking care of the children to come?

The Child in You

Not long ago, all eyes were fixed on the fate of five people who ended up in the depths, helpless, in the uncertain embrace of the future. That was the Titan submersible, but every one of us has been in a very similar role, even if we don’t remember it.

The last trimester of pregnancy is the time when doctors still speak of a “fetus,” although what is inside is in fact an almost “finished” baby. The big risks of pregnancy and miscarriage are supposedly behind us. Yet it is precisely in this period that many of the problems leading to serious complications occur. And catching them in time can be a matter of life and death.

“Lately the emphasis has been on buying incubators and equipment to help resuscitate newborns and treat complications. But in my view we should also talk about how important prevention is, and how in practice it doesn’t happen,” says Dr. Ignatov.

Child’s Play

“It is very important to add more diagnostic options. So that the condition of babies is assessed before birth, and there are far fewer newborns with complications, with oxygen deprivation causing cerebral palsy and neurological problems,” the doctor adds.

Today Bulgaria’s National Health Insurance Fund covers a small number of mandatory checkups and tests during pregnancy. Meanwhile, obstetrician-gynecologists themselves recommend fetal morphology as an additional exam—a mandatory check in almost all developed countries. This safe, noninvasive method detects a large share of the anomalies and problems that pose a risk to the baby-to-be.

And while most future parents do get this exam (those who can afford it and have found a responsible gynecologist to follow the pregnancy), there are many other important checks.

The pregnancy has reached week 28, the last, decisive third. The tests for chromosomal anomalies and the fetal morphology have been done, and they have shown that the baby is developing normally. The most important question now is how it is feeling in its temporary home. Alas, like the passengers of a submersible, it has no way of telling her, and it is important for doctors to follow the signals. Which, however, rarely happens.

The Unborn Hero

“In the last trimester, the most important thing is to monitor the condition of the fetus, because a number of factors, inside or outside the womb, could have a negative effect. They could lead to fetal distress, as we call it. A lack of oxygen to the brain and vital organs, anemic syndrome, reduced oxygen saturation of the blood,” says Assoc. Prof. Ignatov.

Doppler ultrasound is used in many fields where it is important to track the movement of blood through a vessel. In the last stage of pregnancy it is a fitting solution, harmless and noninvasive, for checking the parameters of blood flow in the baby’s middle cerebral artery.

The method is simple and proven to show whether everything is fine… and yet it is hardly ever used in Bulgaria, which is why complications so often arise.

“Nobody talks about it, and few colleagues are able to apply the method. I very much hope patients will inform themselves, take an interest for the sake of their babies, and as a result more colleagues will want to learn,” the specialist says. He is ready to train his colleagues entirely free of charge, as long as they are willing. This type of examination is already part of the courses for specialists held at the medical center where he works.

Children of Mother Earth

“I want to reach these people, for them to understand that it is not up to God whether the baby survives the third trimester—there are ways to find out what its condition is. If it turns out there are signs of fetal distress, of oxygen deprivation, there are many things that could be done! As a last resort, it can be delivered earlier, but that could save its life!” the obstetrician-gynecologist adds.

Either way, for now the examination is performed in a very small percentage of the roughly 60,000 pregnancies a year in Bulgaria.

And although this convenient method is already quite revealing… here we come to the contribution of Assoc. Prof. Ignatov and his team toward making it, and every other form of Doppler examination, considerably more precise.

Math for Doctors

“For the 40 years that Doppler examinations have existed, they have been interpreted with one and the same formula. Our team proved that it is wrong and that it is time to replace it with another, much more accurate one,” the doctor explains.

When blood flow through a vessel is monitored, the line reaches an obvious peak before heading down. For a long time, that was believed to be where the line between systole and diastole runs—systole being the moment the heart pushes the blood out and it passes through the vessel under rising pressure, diastole the moment the heart relaxes and the pressure in the vessel falls. The pressure at this peak, referred to as the “pulsatility index,” is the indicator doctors in various fields track. Including in examinations during the last third of pregnancy.

Sometimes, though, what matters most is invisible not just to the eye, but to the instruments as well. In recent years it has become clear that the boundary between systole and diastole is not the obvious peak! Shortly after it, once the pressure has started to drop, there is always a second, lower peak, and that is the true boundary.

Eyes Wide Shut

Although this phenomenon has been proven, medicine is slow to get used to the change. And now Assoc. Prof. Ignatov and his team are offering another important solution, one with the potential to make diagnosis far more accurate!

Over the years he has examined many pregnant women, and at first he noticed a correlation intuitively: the larger the area under the curve after the second peak, the greater the risk of a problem.

A month ago, after years of research, his scientific paper on the subject came out. In it, Assoc. Prof. Ignatov and his team propose a formula for calculating the area of the shape formed after the second peak—in diastole.

The pattern: in unborn babies whose shape falls within the normal range, the pregnancy ends calmly. Outside it are children in whom further tests confirm a problem, and timely, adequate measures are needed.

Interest in the topic is high; the paper has already been cited and discussed by professional communities around the world. And Assoc. Prof. Ignatov is preparing the next big step—an international study across different countries and hospitals, involving tens of thousands of patients who would be followed up, so that the new formula can be proven conclusively and turned into the gold standard.

The Bottom Line

But how could no one, for decades, have noticed that the most accurate indicator was not being used to analyze Doppler examinations?

“This boundary really has been misread for the last 40 years,” the doctor says. “It may sound strange, but in medicine it’s not unprecedented. There are many cases where we did something wrong for a long time, or used an unsuitable method. The phenomenon was right in front of our eyes for decades, and no one thought to use it. I, too, didn’t ask myself critically for a long time whether all this held up. Until at some point, like most ideas that come to people, I slapped my forehead. ‘Well, what if…?’ What followed was 8 years of work. We had to handle it purely mathematically and methodically, to recruit patients. And to prepare the publication so that it met the extremely high standards of today’s renowned medical journals in our field.”

Pressure Cooker

“This area measurement is a qualitatively new approach to interpreting all Doppler examinations,” the doctor says. “Introducing this indicator is a huge moment for us, because it changes the whole paradigm in the fields of medicine that deal with assessing blood flow. That’s 70 percent of medical specialties, and veterinary ones too.

This phenomenon, called the ‘diastolic deceleration area,’ exists in all vessels relatively close to the heart—in the head, the arteries to the arm, the pulmonary and renal arteries, even the uterine arteries. So all specialties, such as cardiology, gastroenterology, endocrinology, internal medicine and pulmonology, stand to benefit from studying how this indicator could be useful in their practice,” the doctor sums up.

The method has been patented here, and Assoc. Prof. Ignatov is determined to do everything possible for it to remain a Bulgarian patent.

This is not his first life-saving innovation. For almost a decade now, doctors have been using his platform for automated assessment of the results of another important examination during pregnancy—cardiotocography.

As Assoc. Prof. Ignatov himself says, what matters from here on is finding more like-minded people—among expectant mothers, and as a result among his colleagues. Because many, many lives of unborn babies could be saved.

Can there be anything more important than that?

What happens when artificial intelligence takes on its next big job: creating… artificial intelligence? What if we asked the famous ChatGPT to “create” a new neural network to solve a specific problem? Is it possible for complex algorithms to create their own successors? What would change as a result? Might this not lead us to the next step: an absolute AI, capable of solving any task at all?

These questions have many possible answers, but while we are asking them we may miss something important: systems already exist in which AI oversees and assists the process of creating its own “kin.” What is more, it does so in order to build solutions that are more secure and safer for people.

The Good, the Bad and the Ugly Robot

Ever since the Terminator arrived—and in fact several millennia earlier, thanks to the god from the machine—humanity has had one and the same ultimate worry about its relationship with machines. That they will take control. That they will manage to make conscious decisions, and it will not be within our power to stop them. The archetype not only survived but blossomed in the years when the famous term “artificial intelligence” took hold.

We have already asked whether the day is approaching when algorithms will learn to create software on their own. In one way or another, this is already happening: they spare programmers quite a few tedious tasks. Even if they are still far from real software engineering in all its fullness of multilayered problems.

Then comes the next important and interesting frontier. What happens if algorithms are capable of setting themselves the next task? Of programming and developing artificial intelligence.

Even Grandma Knows

Self-replication is a phenomenon we always associate with biological organisms. In other words: if artificial intelligence achieves it in one form or another, that will certainly be one more sign that our artificial creation keeps scoring points. That it keeps taking steps forward in its evolution.

The singularity is that moment when computers turn out to be “smarter” than us. Naturally, whether we ever reach that stage is a subject of serious debate, and we have already discussed it in detail.

Both of these—self-replicating artificial intelligence and the singularity—are concepts from a possible future. In this field the enthusiasm sometimes definitely gets out of hand, so let us step back from fears and dreams to the present day. To tell you about several interesting projects showing that algorithms can not only help create their kin but are already doing it. And not instead of people, but by helping us where they are stronger than we are: in their impartiality.

Who Will Guard the Guards

Once again we have to start with a short definition of what the famous AI actually is. Yes, when we talk about intelligence, the first and natural association is always with the human mind. The system that may one day resemble it, however, has a specific name: “general” or “absolute artificial intelligence.” Without that important first adjective, what we have is simply software that in some way resembles human thinking, ready to solve a specific task. Over the past few years this has most often been done through machine learning and the famous neural networks.

But even that term is rather misleading. The machine sits there teaching itself poetry by reading Goethe… Alas, nothing of the sort. We are talking about an algorithm that can process enormous volumes of information and look for patterns. Through carefully chosen parameters, it finds out which indicators matter. And on the basis of all this it solves one specific task, which always boils down to two options: to predict what the next unit of information will be, or to classify the next unit according to various criteria.

At first glance a simple solution, yet in some areas it has genuinely achieved the kind of perfection that earns it the label “intelligence.” For example, when it comes to facial recognition, driving autonomous cars, even creating works of art.

In some form, neural networks do exactly the same thing. The difference is that they involve a series of algorithms arranged in layers, which can discover far subtler patterns. But once again, you cannot say that one algorithm creates the next.

We Will Build a Factory

How, then, do we get from these principles to the next step? To artificial intelligence helping create its own successors?

One of the most serious problems in developing algorithms of this kind is reducing prejudice, which you will also encounter under the English term “bias.” More or less, how well an algorithm can do its job depends on how its initial parameters are fed in and how the individual elements or layers of the neural network are chosen. This is also where the big ethical questions arise.

This is precisely the main and hardest work of specialists in the field today. In the early stages, before actual machine learning begins, the creators of artificial intelligence very often proceed by trial and error. So what would happen if other algorithms replaced them in this foundational task?

Caught in the Net

With AI, everything turns into numbers. Whether we are talking about video or simulations in drug development. Sometimes training the models requires millions or even billions of parameters to be processed precisely and repeatedly before the software finds the right patterns.

Sometimes, if the volume of data to be processed is large, this can take even months, despite the enormous computing power of modern machines. That is why one of the first directions in which next-level AI projects are expected is creating systems that can themselves skip many steps. That can optimize existing algorithms and simplify them. The field is called “hypernetworks,” and it has definitely been one of the popular directions lately. Hypernetworks analyze the data and the corresponding untrained neural networks and can make the learning process considerably easier.

Among the pioneers in this direction is a team led by Boris Knyazev of the University of Guelph in Ontario, Canada. In 2018, he and his colleagues developed a graph-based hypernetwork whose goal is precisely to find the best neural network architecture for a specific task. The next generation, GHN-2, appeared a year ago and is able to take in and analyze the parameters of 500 different networks and match them with the possible next tasks for which a solution is being sought. In other words, if the system works as well as it promises, it saves 500 network trainings that developers would otherwise do one by one, and working time shrinks drastically.

I Have Raised Myself a Monument Not Made by Hands

All this has many dimensions, not only in terms of time and effort but also in terms of saving the huge energy resources that supercomputers often need to run.

The truth is that we know far too little about what actually makes deep neural networks so effective. As we have mentioned before, we feed them data and rejoice at ever more successful results, while they remain a black box—we do not know exactly what happens in the middle. But things get more complicated if we add hypernetworks. If they happen not to do their job well, we have no way of knowing that it happened, and above all why. We will have bias, raised to the next level…

A Robot Weaves a Fence

Let us go back to the good old Terminator for a second. After all, what we had there was an encounter between two absolute artificial intelligences—one wanted to destroy humans, the other to protect them. Well, we now have something similar as a solution in today’s AI, too. A startup with Bulgarian involvement is developing a neural network that watches over others of its kind and protects us from them getting out of control…

The startup is called Tenyks, and at the start of 2022 it raised $3.4 million in funding with its unconventional proposition. Serious names appear among the investors, for instance John Taysom, the first person to back Yahoo financially, in 1995.

The founder of the company and author of the idea is Botty Dimanov, a doctoral student at Cambridge. The platform developed by him and his two partners is aimed at developers in machine learning. With the help of their application, they can build their projects faster and more safely.

The platform allows AI-based systems to be tested much more easily and reliably. To get through the initial analysis of the data they receive more quickly, so as to create more targeted solutions in the chosen field. The goal is also to develop models that are more independent of human error, of being misled by the initial information depending, for example, on our personal preferences.

Hooked on Bias

Tenyks takes the models developed by programmers and evaluates them according to various parameters. It looks for their weak spots and for where that notorious prejudice shows up—the “bias” specialists so dislike. In other words… once again we have an AI that directly helps create its kin.

“Every time technology reaches the limits of the impossible, the next category of software solutions appears. Computers developed their graphical interfaces, and the internet its search engines. That is why I believe AI will have similar platforms that will allow us to take its development to the next level,” Botty Dimanov told the site The Recursive.

One of the reasons the subject is ever more topical is the way the data itself is processed. “AI development today is shifting from work centered on the model by which information is processed to work focused on the information itself,” says Rick Hao, one of Dimanov’s colleagues. This is exactly where the team’s application comes in—it helps engineers with the initial processing and with analyzing the steps to take in order to improve how the algorithms work.

Robotic Zen

Robots don’t understand poetry? We could argue about that for a long time (and we have, here). “Paired Open-Ended Trailblazer” sounds more like Vogon poetry, but it abbreviates to POET. This is the project of Uber AI specialist Rui Wang, and once again it is connected to our subject.

In short: the idea is again to create a hypernetwork, but one that tests and builds on algorithms in a different way.

Since the author comes from the East, he describes the way his system works as a kung fu contest. The algorithms are given tasks and pitted against each other, and not only does it become clear which is better, but each of the “contestants” progresses and develops in what it does. “In the end, a complete, true kung fu master walks out of the training dojo,” Wang says.

The system starts with a simple task, moving on to each next stage with new knowledge and facing different obstacles. When it succeeds or fails at a given stage, the “competitor” moves into an entirely new environment. The decision to change the environment at random turns out to be a particularly successful factor.

“POET is based on a paradox,” Wang says. “In life it happens that if you try to solve a given problem, you will fail, and if you don’t try, you are much more likely to succeed. Sometimes that is exactly how evolution happens in nature, so it is possible to achieve something similar with artificial intelligence.”

Darwin Makes Darwin

According to the team, it is exactly projects like these that lie on our path toward creating the long-awaited absolute AI. One that will be able to solve various tasks, not just one specific task, as, we have said, is the case today. So however distant the future of such developments may seem, their roots are already here.

“It is time to start creating algorithms that contain a certain form of intelligence from the outset and to watch them create the next ones on their own until, eventually, we reach absolute AI,” says Jeff Clune of OpenAI.

“The truth is that for now it is just a fantasy. But that is mainly because no one knows exactly how to create it. Progress in this field depends on people and happens step by step. Solutions that have already been discovered and are familiar get combined in different ways, gradually improving their success rate.” Clune says that in this way we are creating ever better individual building blocks, from which we will struggle to construct the building of absolute AI on our own. “And perhaps it falls to the algorithms to take on the hard task of putting it all together.”

Small Children, Small Troubles…

And what happens after that? As Jane Wang of DeepMind says, one of the main advantages of involving AI in creating AI is that it will come up with design ideas and techniques humans would not expect. “But not all surprises are good ones. If you harness AI to create something you yourself don’t understand, it is much harder to control it and to predict where the problems will crop up.”

The ventures we have told you about are the decisive first steps toward creating absolute artificial intelligence. But are we ready for the next ones? Not so much technically as civilizationally? We will keep looking for the answer together in the next Digital Stories…

Will the future really force us to give up meat? Or will we simply eat meat that… was made without killing an animal? Will technology soon let us understand more about how our best animal friends see the world? Will it let us talk to them…

Our relationships with the other species on the planet have always been more layered than we realize. While we have turned our greatest natural enemies—the predators—into little more than decorations of our daily lives, the “small fry” like the coronavirus remain an unpredictable problem for our species.

And yet the most fascinating remain our ties with our closest “relatives”—the mammals and the other links that have climbed high up the food chain. We give them souls and make them part of our daily lives… while the vast majority of the planet's inhabitants rarely pass up a chance to snack on them.

Our relationships with the other species on Earth are yet another field where technology promises striking news, and in the foreseeable future at that.

The Steak Is Dead, Long Live the Steak!

The young Zuckerberg liked to boast that he belonged to the school of thought holding that there's nothing wrong with eating meat—as long as you have personally killed every animal you put on your table. He even showed photos… Then someone apparently decided the idea wasn't great for his image, and he switched to combat sports, where, they say, he turned into a real predator.

The fact is, we like to run away from this subject. It's convenient when an appetizing steak appears on the plate, its aroma stirring not only our refined palate but also something of the old instincts… And yet, to get there, there has been a killing. Most of us conveniently delegate that step down the line, with no desire to find out exactly how it happens.

If we look at it from an evolutionary angle… Aren't we supposedly the most advanced species? Is it “well-mannered” to treat the others this way? And what if the next link in the chain—artificial intelligence, for example—decides to take the same approach?

It Never Grew, It Never Grazed

Let's leave science fiction aside for now: there is some inner conflict in eating meat. Ask the children. We tell them fairy tales about ugly ducklings and call our own kids “little chicks,” and then we sit down in a restaurant to snack on… yes, little chicks, whose existence hasn't always been the loveliest.

Add to this the topic that has lately become obligatory—environmental damage. Meat production is responsible for a huge share of our civilization's carbon footprint.

There's been a lot of talk recently about turning to proteins from the lower floors of the evolutionary ladder. Since huge numbers of people in Southeast Asia are used to nibbling on insects, maybe we in the West will have to get used to something similar? It hardly seems a challenge for our digestive system—humans are omnivores. Especially in our part of the world, where we survive everything that ends up in our frankfurters…

Tamagotchi

Jokes aside, there may be plenty of arguments in this field, and most of them are culturally determined. Is pork really forbidden in Islam because the religion took hold in warmer latitudes, where pork is the meat that spoils fastest? Are our delicate Western stomachs really not evolutionarily suited to locusts as food?

Maybe we don't even need to venture into such speculation!

In recent years, technology has been bringing good news. It makes sense to look for a substitute for meat, and while all the attempts to imitate it with soy, chia or mushrooms evoke only distant associations, it looks as if we'll soon have meat that is completely real, only… not a single animal has “suffered” for it.

Off with the Cell's Head

“Lab-grown meat” sounds deeply unappetizing. But then “belly soup” isn't the pinnacle of marketing either, if you're introducing shkembe chorba—the tripe soup Bulgarians swear by—to your children, and tripe… is, with good reason, a favorite.

Let's look at it from another angle. What is meat? On the one hand… a carcass. On the other—simply a collection of animal cells. So what if we take cells obtained without anyone being slaughtered and teach them to divide… wouldn't that be a natural process, even if under laboratory conditions, that leads to a fragrant little steak?

It's already entirely possible. Yes, skeptics will remind us to be careful with such technologies, because even the most revolutionary invention can turn out to be dangerous. And we may find out far too late. Nor will it seem particularly appetizing if you see the big steel vat where the cells divide… As if the slaughterhouse that supplies the ham in your fridge were such a pleasant sight.

The steel vessels are called bioreactors, and no one dies in them; the cells divide contentedly, happier than any free-range hen. The technology has advanced considerably. Even the FDA—the US food agency, famously fearsome with its regulations—has approved the first cultivated meat product, “chicken breast” grown by the California company UPSIDE Foods, as safe to eat. The next step is clear: for these products to reach the market and fight their way past the stereotypes.

Whitey and Greyling

They'll succeed, in my view—both digital marketing and the Overton window are capable of miracles. What's more, generated meat is already being sold to gourmets: Singapore became the first country to issue such a permit.

As for Upside Foods, the startup's ambition is for its “chicken breasts” to appear in restaurants as early as 2023, and in stores five years after that.

“This is real meat, grown directly from animal cells,” says Upside Foods founder Uma Valeti. “These products are not vegan, vegetarian or plant-based—they are real meat, just made without animals. The production process is similar to brewing beer. Only instead of growing yeast or microbes, we grow animal cells.”

A sample is taken from the relevant species, the cells are placed in a controlled environment and fed nutrients, thanks to which they begin to divide.

Flesh of the Flesh

But why is chicken breast the first dish? Upside Foods doesn't say; I have a hypothesis. The meat is homogeneous enough to be convincingly recreated. For pork ribs and chicken wings (or the other way around) we'll have to wait for the bioreactors to advance—those involve more varied textures and types of cells.

And might 3D printing be the way forward? It seems it would be easier to create more complex structures that way.

In April, the Israeli company Stakeholder Foods printed the first three-dimensional fish! No wonder—that part of the world has long been known for feeding a great many people with just two fish and five loaves.

To the Animals, with Love

Shortly after the factory opened in the city of Rehovot, Prime Minister Benjamin Netanyahu tasted the first portions. “There will soon be new permits for the production of such products and new heights that will change the world,” the prime minister said.

Alas, in this direction we're heading back toward the synthetic; at this stage, what we get would be more of a meat lookalike.

But then… maybe it's again a matter of culture and self-suggestion? There won't be as much fat, and you know the chain from there: cholesterol, clogged arteries, early death or, worse still, middle-aged diets.

Or, even worse, the infamous animal gases: livestock farming is believed to account for around a quarter of global harmful emissions.

Got a Cow, Drink Beer

Let's say the question is settled, especially if we get far enough to start printing sudzhuk and lukanka, Bulgaria's beloved dried sausages. But what will we do about milk? Have you ever wondered how cows manage to give it to us all year round? I don't recommend opening documentaries on the subject; it definitely doesn't happen with any eagerness or harmony on their part. Let's hope nobody shows those scenes to artificial intelligence, or it will have good reason to take it out on our species.

Milk can be made through fermentation processes similar to those in the meat bioreactors, ambitiously promises another American startup born out of scientific research—Perfect Day. Once again, the bet is on biomass from animal cells, which creates milk through precisely controlled fermentation. And here, too, the popular explanation is that the process resembles brewing.

Yes, for now they only produce powdered milk, but it's already being used to make ice cream. Another pioneer comes from Australia: All G Foods raised 25 million Australian dollars, promising that within seven years it will produce cheaper milk indistinguishable from cow's milk.

A Horse for a Hen

There's no word yet of a solution for artificial eggs, but let's say that's an area where we can manage without the animals suffering excessively. They even come out ahead, sparing themselves tiresome offspring like “My dear sir.”

Since we touched on livestock farming's enormous carbon footprint… I don't know about you, but I've always found it hard to imagine that the gases released by cows could be such a major factor. I've also always wondered how exactly the measurements are made.

Bill Gates, however, apparently has a better idea. Because months ago it emerged that his main investment fund had set aside $12 million for a small startup called Rumin8, which is developing a new type of feed for ruminant livestock.

The innovative feed is based on red seaweed pellets and reduces the methane in the gases cows emit.

If Only They Could Talk

“And it spoke with a human voice.” No, not Bill's experimental cows, thankfully. But this is such a familiar motif from fairy tales; we've always been inclined to attribute human qualities to animals, to give them souls… And hasn't the time come not only to understand them but also to start talking with them? Will we like what they have to “say” to us?

The development of artificial intelligence brings breakthroughs in countless fields, including one that, sadly, isn't talked about enough—mind reading. Algorithms manage to find the patterns between data on brain activity and what we see, and they are gradually getting better at ever more precise associations. And if, where humans are concerned, this raises very serious questions, in our relationship with man's best friend and his colleagues it opens up interesting prospects.

We Had a Good Life, My Little Horse

Will we learn to “read the minds” of animals? Everything suggests we'll soon know more and more about how they perceive the world and how they communicate with each other. All the memes about what the cat or the dog has to tell us and what it thinks of us could become reality. We might even… check whether characters like Rumen the Cat really think what they write online.

Even the experiments of Musk and his team with the Neuralink interface, which “reads” the brain activity of monkeys, give interesting food for thought. Once again, both benefits and dangers loom. It would be great to know when an animal is in pain so we can help it. But imagine, too, the potential military applications of this kind of technology.

We already know that bats use sounds to argue over food, tell the sexes apart and call each other by name. Parrots and bonobo chimpanzees learn words and associate them with objects. Dolphins understand differences in word order, and bees communicate fully through sounds and movements. What will happen when we begin to “translate” their signals far more accurately?

Of Mice and Men

The Earth Species Project, or ESP, is a California startup working on various forms of decoding animal languages. Its ambition is to lift the language barrier between humans and animals for good. The researchers are searching for the interspecies Rosetta Stone across a wide palette of factors. They analyze the sounds animals exchange in different ecosystems, as well as the background noise. They work with more than 40 ecological and biological institutions to keep filling their ever-growing database, which is processed with the help of artificial intelligence.

The algorithms analyze “bioacoustic” sounds—those made by individual species—and “ecoacoustic” ones, which include everything recorded from an entire ecosystem. So far the greatest successes have come with the large inhabitants of the sea. The researchers can distinguish the sounds made by different whale populations and already understand the meaning of many of the signals.

Here we'll surely soon apply the possibilities that new technologies offer in translation as well. Large language models are increasingly skilled at translating from and into languages they haven't been specifically trained on. However anthropocentric it may be… couldn't we add animal sounds too? The experiments with whales show that it's entirely possible.

Will we manage the reverse? To dictate to our smartphone, “Bring me a beer,” have it translate that for the dog, and see our best friend come trotting back with two cans—one for himself?

Hardly. But we will find out whether beasts really have something like feelings… We have them; algorithms are getting better and better at pretending to have them. Interesting news is on its way from the meeting of technology and the living world. It will help us learn more about ourselves as well. As long as we learn to listen. To people and animals alike…

“The Game is Over.” That is what researcher Nando de Freitas declared on Twitter in May 2022, announcing big news in the field of artificial intelligence, news that stayed off to the side of all the noise. Scientists were still arguing over whether artificial general intelligence could exist at all. Behind that term lies an algorithm capable of solving a great many different tasks, much like the human brain.

And while they argued, it seemed to turn out that… the argument had already been settled. That terse tweet announced the arrival of Gato AI, the first contender for the title of “artificial general intelligence.” A step that was expected to be at least a decade away, and one that many considered outright impossible.

The news, however, didn’t attract much attention. Unlike ChatGPT, which appeared half a year later and has been monopolizing the spotlight ever since. Well, it managed to turn heads by showing, for the first time, an enormous number of users just how advanced the technology really is. And how we are getting ever closer to the next giant step. One that seems at once logical and… so impossible. Artificial general intelligence!

A General Change

Yes, we all hear its name far too often; by now even the straw in our beach cocktail has artificial intelligence. And yet there’s no denying that this field of knowledge is extraordinarily dynamic, advancing at breakneck speed in many of its applications.

And so we talk more and more often about the next giant step. An algorithm that isn’t merely ready to perform remarkably well at the task it has been given, but is able to solve problems of every possible kind.

Gato came along to settle (perhaps) this long-running debate, to change the game entirely. To show that there can be a universal algorithm for different tasks… one similar to humans. Yes, neural networks, the high art of machine learning, strive to imitate the way our brain works. But while we are capable of solving all sorts of tasks, until this step algorithms were confined to a single one. By all appearances, we are done with that.

Jack of All Trades

When they are given exactly the right task, algorithms are capable of wonders. They can analyze enormous volumes of information and then accomplish their goal. And that goal can be of only two kinds. Either they receive the next “piece” of information and determine what it is, or they try on their own to predict what comes next in a given sequence. That’s all; practically every task we set them today boils down to this.

The same goes for the much-hyped large language models—GPT-3 and 4—and, in full measure, for their beloved sibling ChatGPT. It, too, can impress with a wide range of applications, from machine translation through chatbots to generating computer code. And still: in essence, outside the bounds of that specific task, it also belongs on the list of competitors with a single event. Because what it does is process information and, in response, give us its closest possible guess about what will follow, based on the patterns it has found. It, too, works in one specific area: natural language processing. Artificial general intelligence is the next step.

DeepMind is the Google project that once made Musk worry about the future, because in his view it was being developed without sufficient oversight and had access to the vast troves of knowledge of the universal search engine.

Well, perhaps that warning is worth keeping in mind as we turn to the subject at hand.

King and General

On May 14, 2022, Nando de Freitas posted the landmark tweet saying the game was over. Of course, he added an important caveat: “It’s all about scale now!” In other words, we now have an algorithm capable of solving all kinds of tasks (which is why it’s called general), not just the one specific task it was built for. All that remains is “only” to teach it to work at larger scales than the ones it handles so far.

The news mattered so much not only because many specialists didn’t believe it was possible. But because it marks a decisive step on the road to an artificial intelligence that could be indistinguishable from a human one.

Nobody is saying this will happen tomorrow, but the arguments are piling up that one day the technology will be able to pass the famous Turing test, conclusively convincing its human interlocutor that they are talking to another member of their own species. Even de Freitas admits that we are not as close to that step as we’d like. What matters more, in his view, is that we now know it is entirely achievable.

Alongside the landmark tweet, the team published a scientific paper and a blog post presenting the new algorithm in detail.

Gato is named after the Spanish word for cat. And it is definitely as clever as a tomcat (like our friend Rumen, for example).

Multicooker

This little gif shows the many different tasks the clever cat can handle:

The picture didn’t impress you? Just a bunch of worn-out games from an ’80s computer? Fair enough, a little more explanation is needed.

As mentioned, none of the AI projects existing up to that point had been able to solve tasks of different kinds. And games like these turned out to be the perfect field in which to look for general AI, simply because they require different interactions. Gato turned out to be the first “electronic player” ready to tackle challenges that were child’s play for the teenagers of that era.

On top of that, the cat can write poetry and stack blocks by controlling a robotic arm. One and the same neural network can chat, recognize images, and who knows what else.

The Cat’s the Boss

“From here on, the goal is to make models of this type bigger, safer, optimized, and in line with computing capabilities. We have a lot of work ahead, but solving these problems will lead us to general AI,” Nando de Freitas is convinced today.

Of course, there is also the small matter of figuring out whether, in achieving this, we might be creating a program that will wipe us out as a species.

“Safety is of paramount importance in this kind of research,” Gato’s creator admits. “We must always be able to stop an algorithm like this when it starts making decisions that are too important. And that may be the biggest challenge before us.”

Google has reportedly already developed a special system, a big red button of sorts, so that such problems can always be prevented. So that the AI can be “switched off” if we decide it threatens us in some way.

Here, Kitty, Kitty

Gato can not only perform more than one task at the same time, it also does so reasonably well. In some of its “professions” it rivals algorithms specialized in them, but, alas, that is far from true for every task.

The team tested its contender on 604 different tasks, and the cat completed 450 of them with a success rate above 50 percent. High, but still a long way from what is being sought.

Because of the way it works, Gato is considerably “weaker” than many of its rivals. The basic unit by which algorithms of this kind are “measured” is the number of parameters in the neural network. While GPT-3 has 175 billion, Gato “learned” with just 1.18 billion.

Puss in Boots

Naturally, its creators’ claims were followed by quite a few conflicting opinions. According to some researchers, Gato falls far short of the requirements for us to accept it as a forerunner of general AI. It is, rather, a combination of straightforward models pretrained on data. Yes, it can perform 600 tasks at once, but that makes it more like a console with 600 games than a game that can be played in 600 different ways.

The approach to building it is interesting: the cat was pretrained on all sorts of varied data—texts, images, maps—converted into tokens. This runs against the usual approach, in which a neural network’s “homework” contains only objects of a single type, images, for example. And the fact that it still produces good results opens up yet another line of thought for scientists. It gives us additional insight into the way deep neural networks work.

Tom and Geoffrey

Talk of artificial general intelligence grew even louder with the explosive popularity of ChatGPT. Some of the pioneers and biggest names in the field, such as Yann LeCun, are skeptical that it is near. Until recently, Geoffrey Hinton was also on that list, but… the dramatic statement with which he announced his retirement made it clear that this is no longer the case.

Of course, sometimes it comes down to definitions; there are quite a few of what exactly “general” means, and at times they contradict each other. According to some, it is the ability of an algorithm to perform every mental task a human is capable of. And here we are still light-years away, when it comes to creativity, free will, irony, and abstract thinking, for instance.

Another definition sets five specific requirements for the title of “general AI.” It must show creativity and understand natural languages. It must perceive sensory information, have good motor skills, and move successfully through space. With the exception of creativity, the rest sound fairly achievable along the path the clever cat has taken.

A third definition of the term simply requires an algorithm that can perform complex and varied tasks. Here Gato is definitely already a good candidate that meets the requirements.

And does this step truly bring us seriously closer to the bigger goal—an algorithm approaching human abilities? We can still speculate more than we can be certain of anything. The only certainty is that we live in interesting times, and we hope the world of technology will bring big news, but above all good news… So that we never arrive at the other meaning hidden somewhere in the words of Gato’s “father.” “The Game is Over.”

Chat by the Hour

It is worth noting that OpenAI, the creators of ChatGPT and all the other GPTs, openly admit that their long-term goal is precisely artificial general intelligence. With a noble rather than a commercial aim, of course. As the company’s manifesto puts it, “our mission is to ensure that artificial general intelligence—AI systems that are generally smarter than humans—benefits all of humanity.”

It then goes on with even more “specifics”: “AGI could happen soon or far in the future; the takeoff speed from the initial AGI to more powerful successor systems could be slow or fast.”

Recently, scientists from Microsoft announced that in their view GPT-4 shows “sparks” of artificial general intelligence. According to the team, the new generation of large language models displays more general intelligence than previous models. “Beyond its mastery of language, GPT-4 can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting,” they write.

Well, their opinion was met with a fair amount of skepticism, and one can hardly help accusing them of being less than impartial, given the close ties between Microsoft and OpenAI in recent years.

The Parrot in the Pan

And so we have changed the definition quite a bit once again… But the big question remains: is it possible to have a next generation of systems that are not just “expensive parrots”? Caught up in the two extremes—gushing over the enormous progress of this kind of technology or dismissing it—it is usually the nuances that get sacrificed.

That is why, before we part, I’d like to repeat the fascinating view of a leading researcher on the subject. When I asked him about artificial general intelligence specifically, Prof. Preslav Nakov replied: “We’re not ‘there’ yet, but I’d like to believe we can be. The systems are certainly becoming more intelligent, we can see that.

The question is rather what we want to achieve. There are two main schools in artificial intelligence: strong and weak. The weak one says: ‘We want to build systems capable of solving tasks that are considered to require human intelligence.’ The strong one says: ‘We want to build systems that solve tasks the way a human would solve them.’

And here there is a big divergence. The strong school focuses on whether we are really achieving what a human does: do we have deep understanding, abstraction? The weak one exploits the fact that we have no need to imitate the human. If we want to multiply 17-digit numbers, we can do it much more easily and quickly.

The weak school says there are tasks that call for human intelligence, such as recognizing speech or handwritten text, generating or summarizing text. And we solve the task, regardless of whether it is done the way a human does it.

We have enormous success in this weak direction; the question is whether that also gives us progress in the strong one. I believe we will start making progress there too. But it will be slow. These large language models haven’t built some higher form of AI, but on some level they are moving in the right direction. Because there we are talking about solving a task posed in human language, and that is a qualitatively different pursuit.

What we need right now is better understanding. And people realize it. There are limits to computing power, to memory, to the data we can obtain.

We are at a moment of transition from systems that are very good at a specific task to ones that are more universal and to which I can explain in human language what I want. I want a machine that is universal, because the example is the human, and a human can solve many different tasks, and that is part of intelligence. Including the ability to carry experience over from one task to another.

At this stage, the toolkit we have isn’t ready, but I think we are asking the right questions and setting the right goal. So in the long run, I’m an optimist.”

I know what you’re thinking!

Of course, I know nothing of the sort—I have no idea what’s spinning around in your head. It turns out, though, that this rhetorical claim is quietly becoming the plain truth.

Technology can already “translate” brain signals into readable data, and the first breakthroughs are here. Swept up in the progress of artificial intelligence and the notorious GPT, we may miss a huge leap when it comes to the natural kind. Prof. Nita Farahany, a scientist and legal scholar with vast experience, is drawing attention to it.

“Today there are already companies capable of decoding brainwaves,” she told the world forum in Davos at the start of the year.

Are we ready for the moment when someone reads our thoughts? Will it lead to total control, or will it make our lives more comfortable?

Brain Drain

It sounds rather tempting. You merely think about what you fancy for dinner, the smart device “hears” you and makes sure the dish is waiting for you at home. While you drive, it monitors how alert you are, and the moment you nod off, it stops the car. It “reads” your mood and instantly tailors the feed of your favorite social network to match. Finally, it picks out the perfect series, and comfort is guaranteed.

A piece of news weighs on you? Oh, you’ll never see anything like it again. Someone is planning to rob you? Not a chance—his own device has already reported him to the right people.

So far, so good. But what happens if your employer, or your partner in life, gains access to all your thoughts?

At first glance these are plots and questions from science fiction, yet they are quietly slipping out of it, bursting into reality, and very soon we will have to find answers to them.

Hackers of the Human Soul

“You may be surprised to learn that the future has already arrived,” Nita Farahany said in her speech in Davos. “Thanks to artificial intelligence, it is now possible to decode brain activity in ways we never imagined possible. Everything you think, everything you feel, becomes simply data, vast arrays of data that can be decoded by artificial intelligence.”

Her words echoed through the forum of the richest, where the world’s leaders gather to discuss the future. This is not the first time she has turned eyes toward the subject; the researcher has long been trying to draw attention to this rarely discussed issue. What Farahany herself calls “the battle for your brain.”

She is no random voice—she knows what she is talking about, and the proof isn’t just the fact that she was invited to speak in Davos of all places. Nita Farahany works at Duke University, where she is a professor of law and philosophy. Her bachelor’s degree is in biology, and she holds a master’s in biotechnology. Her main field of work is the ethics of technology, especially technologies tied to our future as a species. From 2010 to 2017 she served on the bioethics commission created by then U.S. President Obama.

I Think, Therefore I Am

Is our brain—this complex organ that lifted us to the crest of evolution—really so easy to “read”? Not at all. We still can’t explain how it works, nor replicate it, no matter how often we call the new technologies we develop “artificial intelligence.” It turns out, however, that it isn’t all that hard to capture and decode some of the signals tied to the way it processes information.

The first route is obvious. Although it hasn’t been in the spotlight much lately, the brain-computer interface is the path by which we will connect to computers in the most literal sense—through a chip implanted in the brain.

The best-known effort is the Neuralink project, through which Elon Musk is convinced he will achieve the long-awaited breakthrough… Except that, as it seems, he has lately been far too busy moderating Twitter and working to halt AI development to focus on chipping people. Or perhaps the venture simply turned out to be too complicated?

A Wandering Mind

For now, the serious breakthroughs are coming from the other direction—devices capable of capturing and decoding brainwaves simply by getting close to our heads. Progress in this field is impressive. According to Prof. Farahany, it will very soon give us handy gadgets in our daily lives that can pick up our mood, judge whether we are focused, and tell what we are picturing. And create a host of new challenges…

Filter bubbles, the false comfort of letting an algorithm decide what matters to us… And then come the conscious and the unconscious in all their depth, in images that are hard to imagine being captured and that would make even Freud’s beard stand on end.

Sounds utopian to you? Here is a piece of news from a month ago. Japanese scientists developed a technology that can reconstruct an image a person has seen from their brainwaves. They use data from functional magnetic resonance imaging, and the breakthrough came once they added the capabilities of the latest generations of artificial intelligence.

Stable Diffusion is a platform for generating images from descriptions, much like the more popular DALL·E and Midjourney. This neural network is open source, which makes it a frequent choice for scientific work. The Japanese team further trained the algorithm with data from images shown to four volunteers and the corresponding reactions of their brains—which areas lit up. Each of them viewed 10,000 images, as varied as possible.

A Matter of Vision

Two parts of the brain are active in this process: the temporal lobe is responsible for the content of images, while the occipital region, home of the visual cortex, reproduces the size and general layout of objects.

And lo and behold, the algorithm handles the task beautifully. Working from the data, it proves remarkably good at “painting” the shapes and even the colors of the pictures the volunteers saw. At reading what they see!

Yes, perfection isn’t here yet, but the result is remarkable—see for yourself. All the more so given that these are pilot studies, with a small number of volunteers at that. The accuracy of reproduction is estimated at 80 percent, which led the scientists to write in their paper that “this allows us to effectively read people’s minds. Our method, based on human brain activity, can reconstruct images with sufficient resolution and high semantic fidelity.”

“The accuracy of this new method is impressive,” says Iris Groen, a neuroscientist at the University of Amsterdam.

All of this is wonderful! Technologies of this kind promise so much… They will let us communicate with people who are fully paralyzed and have no other way of expressing their thoughts. We will be able to learn more about how the brain works, to “record” our dreams, even to see what our pet is dreaming about…

Thinking About Meaning

“We humans should get used to the idea that we are no longer mysterious souls. We are now hackable animals,” Yuval Noah Harari said in a speech, again before the World Economic Forum in Davos, but back in 2020. With his typical vividness, he painted the picture of a totalitarian state, North Korea for instance, that has found a way to control people so thoroughly that it can read their thoughts. Harari even offered a formula: B x C x D = AHH—our biological knowledge, multiplied by computing power and by the data at our disposal, adds up to the ability to “hack” humans.

Well, three years later, according to Nita Farahany, this is already a fact. It is happening with the help of various technologies. Besides the MRI mentioned above, there is the far more widely available technology based on EEG—electroencephalography, in which brainwaves are tracked using electrodes.

The breakthrough also comes with the progress of artificial intelligence. The approach used by the Japanese scientists may prove successful in so many other areas. That way we don’t even need to understand the brain’s physiology and workings all that deeply. It is enough to set modern algorithms loose in their signature role—analyzing patterns in large volumes of data.

Open House

“In the future, and I mean the near future, these devices will become the common way to interact with all other devices. It is an exciting and promising future. But it is also a scary future,” Prof. Farahany said in her speech.

“Surveillance of the human brain can be powerful, helpful, useful, transform the workplace and make our lives better. But it also has a dystopian possibility of being used to exploit. To bring to the surface our most secret and unflattering selves.”

Where is the line? No one knows, but on the basis of the breakthroughs at hand, we can let our imaginations run fairly freely. Could the patterns between brainwaves and, say, a person’s propensity to commit a crime be analyzed? Logic says there is nothing to stop it. But what comes next? Will we end up in a crime-free future, or in a digital concentration camp?

We start with images—what will we “read” next? Emotional state, levels of concentration. What makes us happy and what makes us sad, what we find funny. Whom we will vote for and what we think of the person across from us. Or the password to our email or our bank card…

Brainstorming

In recent years, quite a few scientific studies have shown that ever more complex brain functions can be read. Big technology companies are investing serious money in this kind of research too, Prof. Farahany explains.

Nissan, for example, is developing technology to read drivers’ emotions; Nielsen, to study consumer behavior for more effective marketing. IKEA is researching how works of art affect the brain, with the study gradually turning toward how to sell goods more successfully. In China, pilot projects monitor the brainwaves of factory workers, soldiers and high-speed train drivers.

Farahany expects the first industries to take advantage to be video games, healthcare, aviation and neuromarketing. In her view, we are at least five years away from being able to read brain activity in full, and we may never reach that stage at all. But the time when the technology works for a specific task, as in the example with the images, is already here.

Thrilling Waves

The technological questions are evidently being solved quite quickly, but not so the ethical ones—exactly as is true, in full force, when it comes to artificial intelligence.

We all love things getting ever more convenient, right? It’s a lot cooler to have a vacuum cleaner that does the work for us. Or a feed that gathers the most important things for us. Perhaps it’s no accident that in English this word means not only the list on social networks but also fodder, the stuff livestock are fed. Surrounding ourselves with the news we want to read, with opinions we love or, the opposite, that make us angry, has already fundamentally changed the way we communicate and the way we perceive the world.

All of this could continue with renewed force and in very frightening dimensions once “brain-reading” technologies advance, Prof. Farahany warns.

“Imagine a dystopian but entirely real scenario in which an employer uses the technology to monitor employees—how focused they are, how they do their work, what they think of the clients,” the researcher says. “When you combine brain activity tracking with other surveillance technologies, the power becomes quite frightening.”

Do You Think So?

“All of this has some big advantages. For example, people won’t need to type text messages while driving; they’ll be able to send them with just their thoughts. But the downside is that we suddenly give access to the most private and sensitive information we have… to Facebook, Google and other tech companies, with no guarantees that this information won’t ultimately be misused against us, that they won’t try to manipulate us or change what is in our brains.”

In her view, the way we treat the subject today is telling. No one has time to read the long terms and conditions; we leave our data online with the giants without realizing where it might lead. But all of this moves to a new, even more dangerous level when it comes to the most personal thing of all. Our own thoughts and emotions…

“People have become so complacent and used to handing over their data without seeing the harm in it. We have given up almost every other kind of privacy and personal data; freedom of thought is the one space we have all always assumed would be sacred and protected,” the researcher says. “That is why I fear that what will happen with brain data is that convenience and the ‘wow’ factor will lead most people to jump in without thinking about the consequences.”

The Last Bastion of Freedom

That is exactly why, in her view, it is important to establish the field of “cognitive liberty” as soon as possible. To set ethical limits that, this time, get ahead of the technology, rather than coming onto the agenda only once the consequences are already here. In that case, they are quite likely to be irreversible. As Prof. Farahany puts it, we will then have lost “the last bastion of our freedom.”

The limits should include areas that are off-limits to technologies of this kind. They should guarantee that we will always be the ones holding the right to hide our thoughts, to deny access.

Will Harari turn out to be right in the end? With his idea that we are no longer mystical souls but simply animals that can be hacked…

We have plenty to think about. Yet another technology is on its way for which we, as a civilization, are unprepared. Let’s think about such things more often. Before, at some point, it turns out that someone can see what we are thinking and use it against us…

– I recently came across an article from about ten years ago that said 3D printing would be everywhere: we would be building houses, printing human organs and transplanting them. Why hasn’t that happened yet?

– I think it is happening, but I don’t see it as a single stage. It’s a process that began long ago with the invention of 3D printers, and it’s still going.

Houses are already being printed—there are huge machines that lay down fast-drying cement layer by layer.

The technology is used in engineering and in biotechnology. The first bladders and the first ureters have been made; there are already an iris and a cornea. All of this is happening! Maybe not at the pace we’d like, but sometimes the challenges simply turn out to be bigger than the dreams.

– Which achievements in this field impress you?

– What impresses me about 3D printing is the incredible flexibility. It inspires me enormously—you can create anything, from car parts to all sorts of everyday knickknacks. Instead of buying a fridge magnet, I print one at home, and at a much higher quality.

I’m impressed by the limitless possibilities and the repeatability—with a printer like that you can make 10 identical things at once, which multiplies what you can do. You can change your business overnight. You don’t have a factory that makes one specific thing; you have the freedom to change.

When COVID came, for example, I switched to face shields. I started making them right away, and thanks to that I was able to keep supporting myself as an entrepreneur.

– Today you mainly work on anatomical models made with 3D printing. The idea came to you when you were a medical student.

– That’s right. I don’t like getting up early, and by the time I got to the university I had no chance of getting hold of the specimens, as we call them. The bones you study anatomy on.

On top of that, the bones in use are decades old. You pick up a skull and it’s chipped all over, because it has been handled for so long. Half its structures are simply gone. A student takes it, the teaching assistant comes over and says: “Imagine this structure here, and that one there…”

Am I studying medicine, or am I at art school, that I have to imagine things?

The university’s specimens are becoming less and less usable, which creates serious problems in teaching. That’s when it occurred to me that 3D printing could produce extremely accurate models for students to learn from. Then I did some research, found out the problem is far from just a Bulgarian one, and decided this was a pretty good opportunity.

– You named your prototype Oscar. What lies ahead for it?

– I want Oscar to become the most popular model of a human skull in the whole world. It’s better than all the other prototypes because it’s a 100 percent anatomically accurate copy—you can observe more than 400 structures on it. Its precision is under 1 mm; I’m the first to have made it that accurate. Most people underestimated it as a business, but I think it’s an incredible opportunity.

There’s also an augmented reality app that goes with it. I can show the structures right on the skull itself, so the student can examine them.

What sets the approach apart is the scanning itself, and then printing at a very fine resolution—0.2 millimeters. And, of course, the marketing. Because when you create a good enough product, it can be copied. The next question is who will sell it better. When all of these come together, you get a complete, innovative approach to creating this kind of biotech product.

– How many Oscars does the world need?

– In Europe alone there are 520 universities, with more than 700,000 students starting medical school every year. I work on the project with love, and I know it will succeed.

Oscar is already used at 5 universities—3 in Bulgaria and 2 in Romania—and this summer I plan to make that ten times as many.

It’s made of polylactic acid, a starch-based polymer, the most standard material in 3D printing. The innovation here isn’t in the technology itself but in the model it uses. Anyone can print a skull, but not everyone can print one like Oscar, because nobody else has such a precise model.

It’s a copy of a specific human skull, but I decided to name it this way because of the wordplay—os is Latin for “bone,” and the name is popular and easy to remember. And if it’s painted gold, it becomes a “Golden Oscar”…

– Before that you worked on bioprinting. Progress there seems slower. What’s harder—replicating the structure or the building material?

– The hardest thing is printing the blood vessels that feed the tissue, which is why only small prototypes are being printed at the moment. To make them bigger, you need 3D-printed blood vessels. The difficulty lies in printing the endothelial cells that make them up, because they are very sensitive and the procedure is complicated. NASA announced a $1 million competition for the person or team that creates the first printed blood vessel, because they believe it will be a big step toward taking humanity to another planet.

– Will we one day be able to print brain cells, or a whole brain?

– Yes, definitely! There’s a great book, The Terminal Experiment, in which the author writes about copying human consciousness into digital form. In other words, we will be able to print brain cells, but so what? What’s interesting about them isn’t the cell itself, but the connections they form with each other through synapses.

With brain tissue, the value lies in the psyche. That’s where its expression and its function are. Anatomically speaking, it isn’t like printing a blood vessel. Blood vessels have a clear function—a tube that “delivers” blood from one place to another. Brain cells are very different.

It will be possible, but the question is: what good will it do?

– Transferring our consciousness, for instance? That would certainly change how we see ourselves, and death… Except we still don’t understand exactly how the brain works.

– Logically speaking, the whole psyche, all of thinking, is just neural circuits—a complex of cells communicating with each other to give birth to a thought. If we could take cells and print them into a damaged area so that its function is restored, that would be interesting. But it’s still far too complicated.

Everything will be printable one day. The questions are when, and what the point will be.

– What are the next steps in this field that you can’t wait to see taken?

– The organs that can most effectively solve the problems of tissue rejection in chronic diseases. The kidney—more people suffer from chronic kidney disease than anything else. Then liver cirrhosis, which affects a large part of the population.

We can divide organs into three levels of complexity. The first are flat organs—that’s skin, and it’s no coincidence that the first successes were with skin. The next level is hollow organs, a closed surface—the stomach, the bladder, a blood vessel. The third level of complexity is the so-called parenchymal organs, which have a more intricate structure.

I can’t wait to see the first people with a transplanted 3D-printed kidney, heart and liver, and that will certainly happen within 10 to 15 years.

But the brain… that will raise a lot of ethical questions. If we print a brain, some neurons that start communicating with each other, that means consciousness, a new person.

Big dreams and big goals are the strongest incentive for maximum technological progress.

– Sadly, I think few people today are driven by motives like that.

– Unfortunately. What drives the modern person? Fear. And ambition born of some trauma. Being ambitious means running away from something, not running toward something. Which is a problem. In my view,

a person’s main driving force should be inspiration, not fear.

When a person isn’t self-aware, they can’t recognize what drives them, and they’re run by the algorithms programmed into their mind. Even a man of 50 or 100, if he isn’t self-aware, is an algorithmic child, with an extra algorithm added here and there if something more apocalyptic happened to him—a trauma, the death of someone close.

Awareness is the key issue. When a person is self-aware, they can truly make decisions.

– Will 3D printing be the next paradigm that dramatically extends human life?

– Average life expectancy keeps rising thanks to advances in medicine. But I don’t know why it has to be dramatic.

– Because we want to live, we’re in no hurry to go, everyone wants to make it to 200…

– Depends on whom you ask. A young person wants to live 200 years, but ask the elderly, ask people close to death. Many of them feel tired, they’ve had their fill of life, they feel they’ve completed all their missions. And they’re ready to change the form in which they exist, because the energy of this world is never lost, it only changes form.

– I’ve seen hundred-year-olds who still want to live. Maybe that’s part of the secret of how they got there.

– Exactly.

The length of your life, the Buddhists say, is determined by your desire to live.

– Is that why our nation is so unhealthy, that we don’t take care of ourselves?

– I think the reason is hyper-professionalism. It leads to suffering in the other areas of life. I believe that

a balanced way of life is the key to a long life and to high levels of happiness.

A balanced life means investing your time and attention in 4 areas—your professional life, your own personality, your family and friends, and your spiritual growth. The reason for much of society’s suffering, including physical suffering, is, I think, that we neglect the other areas. Why?

Because of the motivation produced by the hooks of the capitalist way of thinking.

Because right now it isn’t cool to be healthy, to be balanced. It’s cool to be super-successful, to have the flashiest car, to be a super-professional. You have to have your own business, lots of money, seminars. Above a certain threshold of financial stability, your life doesn’t change, even if you have more money. But you forget that.

– Speaking of motivation, you graduated not long ago. What kind of people go into medicine today? What motivates them?

– Most of them aren’t self-aware either. When you’re 18, how well do you know what you want to do? Dreams and ideals. You’ve seen how cool it is to be Dr. Shepherd from Grey’s Anatomy, you want to help people, your parents support you.

Why did I decide to study medicine? I had an emotional reason, a rational reason and an ego reason. The ego reason was that I pictured how cool it would be to walk around hospitals in a white coat with the power to help other people. I only realized that much later. The rational motive was curiosity. I was curious to find out how the processes in the human body work. It’s so interesting! Why is poop brown, why is blood red? Why do we breathe, why can’t we survive without oxygen? Questions like that were going around in my head.

And the emotional reason was that I saved a little child from certain death, completely by chance. It was in front of my apartment building—his mother carried him out in her arms, and I happened to be in the right place at the right time. He had “swallowed his tongue” because of a high fever; he’d had a seizure and his mother had found him like that. When something like this happens, you have to lay the child down and tilt the chin up—that opens the airway and helps him.

– Of all the questions you used to ask yourself, which ones can medicine still not answer?

– The biggest one, I think, is:

What is the meaning of human life? Yes, medicine has one answer—to reproduce yourself.

But that isn’t enough for a self-aware person. We see it as something primal—the point is to pass your genes on, to be a messenger of the future. Beyond that there are plenty of other questions: how does a person’s psyche exist? How does a personality take shape? How does a group of neurons physically create something immaterial?

How is a person’s inner world created, their beliefs? The human brain has always been fascinating, of course. It’s a pretty good computer.

The way it structures and processes information is very efficient, and there’s still no computer that comes close to it.

– Have we evolved in any way as a species because of technology?

– Yes, the way we take in information has changed. But biological change is slower. Biology always follows physiology, which in turn follows the psyche. I believe a person’s way of thinking can even determine their physiological phenomena—it’s called somatization. In any case, when we talk about evolution, we have to say it unfolds over very long periods of time—10,000, 20,000, 30,000 years—before you see a noticeable difference. What can you see in 200 years? Nothing.

As for biological evolution, in recent years it has shown itself in the significant extension of human life expectancy. We’re paying more and more attention to the brain, and perhaps

once machines take over a large part of physical labor, we’ll start getting weaker and weaker,

because there won’t be any need for strength. And more and more self-aware and intellectual.

What did a person think about 200 years ago? How to feed themselves—the focus was on the first level of Maslow’s pyramid. Today you have all your basic needs met, so the evolution of society is focused on self-improvement. More and more attention goes to the psyche, to psychology. Hyper-professionalism, education, learning.

As we become more and more self-aware as a society and as a race, we’ll move to the next level—we’ll start caring not about ourselves but about something bigger. That awaits us within 50 to 100 years.

– Could artificial intelligence overtake us as the dominant species?

– I think we’ll learn from it, if we’re wise enough. We shouldn’t be afraid of it; we should learn how to use it. I’ve thought for a long time about what will be valuable over the next 5 to 10 years. Until now it was having information—knowing things so you could do things. That’s no longer the case; what matters is asking the right questions. Because ChatGPT knows more than you do—what matters is how you ask it.

Then comes the role of critical thinking, because of information overload and disinformation. These are the two valuable skills of the person of the near future—they

have to ask questions and verify that information.

For that, they need skills and knowledge different from what we had before. But it’s important to realize that you can take advantage of technology instead of being in conflict with it. To see the opportunity, not the problem. Opportunity gives you wings; the problem weighs you down.

– These technologies are expected to change medicine dramatically, in drug development, for example.

– Exactly. Artificial intelligence is already 10 times better at reading X-rays than a lab technician. Lab technicians will disappear.

– And doctors? Will GPT make a good GP?

– No. That’s one of the last professions that will disappear. Those are the ones tied to creative thinking. The mechanical will disappear. What will last longest is everything connected to art and everything that involves empathy.

Where is there empathy? With teachers, with doctors.

50 percent of treatment isn’t giving you the medicine, it’s taking the right medical history and suggesting to you that you’ll get better,

even in the placebo effect.

The question is when people will trust a machine to heal them. But that will happen eventually too. Even though machines will be far more successful at surgery, people will still be distrustful. Because we’re social animals; we want to see empathy. When machines learn to give it to us, then we’ll trust them. And they will learn…

– Do you think you’ll ever practice medicine?

– I don’t know—why not? What does it mean to be a doctor? To help. I help a lot of people. I fulfill my mission as a doctor, I just don’t do it in the operating room or by prescribing medication. I help people’s psyches by giving them an example, a direction, and I help future doctors become better through Oscar.

I’ve had a lot of inner conflicts. For a long time my family didn’t support me in what I was doing, either. It was very hard for me to cope with that and to find something to lean on within myself. But I follow my heart, not my brain.

The brain is a machine—a wonderful servant but a very bad master. The brain is incredible at calculating processes, at doing things efficiently and in a structured way. But it isn’t good at making the big decisions about your life. You can’t choose a wife just like that, rationally. You see a person, they haven’t said two words, and they either attract you or repel you. That’s something more, something the brain can’t understand. It’s another sense—intuition. Modern society badly underestimates it! Because the brain doesn’t understand it, and it can’t be proven.

– Isn’t it interesting? We’ve known for millennia that the heart pumps blood and holds no emotions, yet the metaphor lives on.

– Because it’s part of us. We know it’s true, but we deny it. Two hundred years ago people thought a solar eclipse was magic, because the brain couldn’t explain it. So what did we do? We made things up.

Modern science denies many things simply because it can’t explain them yet, and that’s normal.

The point is to be neither overly positive nor overly negative. You have this intuition—use it.

Where do fears live? In the brain. Being afraid is so inefficient. You experience real physical suffering over something that hasn’t happened. Isn’t that silly?

Big decisions shouldn’t be made out of fear. The heart is never afraid. Great people before us have performed feats like that, and great people after us will too. Because they did it through courage, not through ambition. Be brave!

Social networks have become the greatest technological and social phenomenon of our time. It all started with a Harvard kid's idea to swap photos with his classmates, and before long we had all ended up inside.

Then the venture turned into a machine for attention and data. Along came Instagram, a network built on the image, which was quickly bought by the hegemon. Then, quite unexpectedly, the next “game changer” arrived from, of all places, China: TikTok. The platform, built on short (and often rather… ahem, shallow) little clips, became the choice of today's young people. It came to the point where, for the first time in its nearly 20-year history, the hegemon Facebook woke up with fewer active users.

Social networks keep evolving as technology advances, generations change and countless other forces come into play.

So what comes next? What will the social networks that rule after today's giants fade look like? What kind of content will they offer us, and how will they manage to win us over?

It Doesn't Matter What Color the Net Is…

“Networks”—or nets—is the perfect metaphor here. We swim along through life, stare at the shiny bait and, before we know it, we're inside for good. We huddle tightly with the rest of the catch and together we start polluting the water around us with the emotional equivalent of our natural bodily functions. Meanwhile, the people on the other side, invisible to us, sell off the caviar of personal data we spawn, because they are farsighted enough to know that this way we'll stay valuable longer.

And all that changes is the lure. Facebook came with the promise of keeping us close to our friends; Instagram, of saving us from the burden of words and from the hate, and of welcoming the next generation of the young. And with the newest generation came TikTok and the craze for short videos.

Every new kind of platform cultivates its own audience, its own rules and quirks, which quickly show up on the others too.

When one idea for bait works, gradually everyone gets busy copying it—sometimes “creatively,” sometimes outright. When Instagram appeared, the hegemon solved the problem by simply buying it. With the next generation it couldn't do the same, so it just tries to bring in as much of its competitor's approach and type of content as it can.

Tight Lines!

For now, you can't say it's working out too well. That is exactly why it is especially interesting to look to the future and at other intriguing ideas on the horizon.

Yes, maybe if you asked that same boy who dragged us into the first net, and who never quite managed to become society's darling, the future looks pretty clear. The metaverse will be the virtual environment that “beats the game.” It will take us to another dimension and, as Zuckerberg himself often says, the goal isn't to keep us inside longer but for us to spend our time better.

Yes, except that the grand promises of huge investment and rapid progress collided painfully with reality, and for now they're more of a drop in the ocean.

Then isn't it logical to turn our gaze to the other, already established social networks and let them take up the rod?

Big Fish

Hardly. If anything, they have already given all their model can give. LinkedIn, for example, is the place for business, for serious communication; it could never become the mass solution. There is no doubt that over the past decades the importance of more niche social networks has grown—ones that bring people together professionally, by interests, or simply locally, with the typical examples coming from China and Russia.

YouTube is worth a mention too: the platform where people once only watched videos has also tried to look more and more like a social network, and to some extent it has succeeded. Still, it is hardly in a position to take on the biggest players either.

And where does Twitter fit in? Not even a professional fortune-teller could tell you. Will it turn out to be its new owner's visionary network that revives free speech, or will it collapse under the weight of expectations and his strange moves? Let's hope for the former, but…

Little Goldfish…

Making a social network isn't hard at all… just ask that same Harvard kid (not our own Harvard boys, the Bulgarian politicians who studied there). Or Donald Trump. Not that his Truth Social has stood out for any special achievements or technical solutions, but it's one more example that in today's online world it isn't all that hard, technically, to create something that quickly becomes huge.

As long as you have a good idea and manage to show it off.

The venture is also quite dangerous: you can crash and burn before your time, and it has happened to the biggest. Perhaps you remember Google+, the app that was going to beat Facebook? Or MySpace, the big rival that was neck and neck with it in the early years of the fishing battle?

To a large extent, the evolution of networks has gone hand in hand with that of the internet itself. Content overload led us to pictures. And then our inability and unwillingness to take in longer, deeper content brought us to short, not overly substantial clips.

“When an app focuses on short-form content, it really can't go wrong today,” says Nora Mati, a trends analyst at Uptime App who previously did the same for YouTube. “The problem, though, is that apps today are easily replaceable. If you take away TikTok, someone will very easily and quickly find an alternative.”

Sprat or Whale?

The new ruler won't give up without a fight. TikTok has only five years of history and has already racked up 1.5 billion users!

Despite the efforts of authorities in the West to tarnish its image, the Chinese platform shows steady user growth there too. Its office in California is WhatsApp's former headquarters. Its teams include dozens of people with experience at the other big companies in the industry.

One option is to go straight from the TikToking comedy to the horror. One of the platforms, Triller, is very similar to TikTok but focuses much more on video editing with the help of AI tools. Its investors include Snoop Dogg and Eminem, and among its managers is Josh Richards, an 18-year-old marketing guru with 20 million followers on TikTok. In recent months the app has been climbing the charts fast.

So do we just want more of the same bait? Hardly.

Groundbait

How could content possibly get even simpler or quicker “to consume”? The trend can hardly keep going in that direction; we have reached some sort of ultimate extreme.

What then? Perhaps the sequel comes from a different trend, again tied to the history of the global network. As we've discussed, if the first era of the internet was about static websites and content, and the second about user-generated content, then the still-emerging web3 should be the age of decentralization. Here that could mean one of two things: either the sunset of social networks, or… social networks that work in a decentralized way.

An example in this direction in recent years is Discord, with its 100 million users. The platform makes communication fast and convenient while also bringing back some of the romance of the days of forums and primitive chat rooms.

Tangled in the Net

At first it was called “Slack for gamers”; today it is much more, and it's no accident that the platform is valued at $15 billion. Discord certainly achieves decentralization: you communicate only with the servers that matter to you and where you find meaning.

Will it manage to become the mass solution in the fishing for audiences? Not very likely. It's too complicated for the average user, and in essence it offers no new type of content.

But something has to come next. If nothing else, because the following generations are also boldly moving into TikTok, which always means the young find a new place to “escape” to.

Poparazzi is a social network that racked up 5 million downloads in its first year, with 95 percent of its users between 14 and 21. Its creators stress that the app is the exact opposite of what Instagram offers. Namely, it takes communication back to where social networks began—easier, faster interaction with friends instead of consuming curated content.

Mostly photos and videos are shared, with no need to write long texts. Users create their own boards, which only people they know are allowed to post on. That way friends—or “paparazzi,” as they're called here—communicate in an environment shielded from prying eyes.

Here, Fishy, Fishy, Fishy

The list of similar projects also includes Yubo, Locket and LiveIn. They all bank on the idea that the big companies' platforms are no longer a place to meet friends from the real world.

Also standing against Instagram, and TikTok too, comes BeReal. As the name suggests, there's no reverence here for gloss, filters and polished photos that leave you unable to recognize your favorite influencer if you bump into them in person. Today the platform, which started in France, has about 3 million subscribers and is quickly climbing the download charts, Bulgaria included.

Interestingly, users can post only once a day, and only within a two-minute window chosen by the app. You get a notification and must immediately upload a photo or video from wherever you are. Others react with emojis or with a short clip of their own. The content disappears from the walls after 24 hours and stays only in the user's personal archive.

Under a Big Stone, a Big Fish

Another interesting example that cuts “across the current” is Mastodon. The logo with the elephant's great-grandfather squares off directly against Twitter's little bird. And that's no accident: quite a few of the users who abandoned that network because of its new owner switched precisely to this rival. Its user base grew to 700,000, with 230,000 of them joining in just the week after Musk barged into his new acquisition carrying a sink.

The network has actually existed for six years, but apparently it has only now hit the right moment…

Mastodon has no ads and no centralized management. New posts appear not at the whim of a blind algorithm but chronologically and according to each user's personal settings—you can sort topics by priority and choose the principle by which posts are ordered. Of course, the main problems come up once we start talking about content moderation…

The venture sounds quite sensible, but whether it works effectively we'll find out when (if) the number of subscribers grows. Meanwhile, Twitter's creator Jack Dorsey has also picked up his spinning rod, announcing that he is working on a decentralized platform called BlueSky.

Going with the Flow

Another suspect is not a new solution at all. Twitch has 140 million users and has been around for more than 10 years, but it has made a splash only in the last few. Video is shared here too, but the focus is specifically on live broadcasts. A similar contender is Caffeine, where you also “broadcast” live to friends and fans.

Some are looking for the next big contender in audio content. And there is a certain logic to that, rooted in the success of the podcast genre in recent years. It turns out people enjoy getting information by listening while they do something else.

An interesting new contender is the social network Clubhouse, which in two years has gathered 10 million weekly active users. It's about sharing audio in real time, but… didn't they invent radio a century and a half ago? Still, the niche evidently exists, since lively conversations on all sorts of topics never stop flowing there.

In Murky Waters

Here are a few more possible answers:

Stallios relies on paying a dollar for every person you bring into the network. But we know this kind of fishing scheme in our parts—just ask the Bulgarian pop-folk singer Volodya Stoyanov about his early days.

Octi moves communication into the world of augmented reality, with the idea of using it to help people meet offline.

CloutHub is something like a modern Hyde Park—a place for cultured, intelligent discussion and debate on all kinds of touchy subjects.

HalloApp lets you communicate only with your family and acquaintances, without collecting any personal information.

Whisper, meanwhile, is… an anonymous network. Users post a statement—true or made up, as text or an image—and a discussion begins. No friends, no followers, no likes. But yes, the main idea here is for the conversation to go beyond the personal, and anonymity is guaranteed.

The Old Man and the Sea

And yet… we keep going either with copies of familiar ideas, or with a return to old solutions, or with the exact opposite of the platforms that exist now.

Experience shows, however, that the breakthrough comes from bold and unexpected ideas.

What they might be is hard to guess; not even the man with the sink has that kind of foresight. But new and interesting things are certainly “baking” in the online world, and the winners will be those whose idea manages to catch the wave…

What will the next irresistible bait turn out to be? Will the future Platform once again be “free,” or will it have a subscription and win precisely because of that? Will it allow anonymity, or will it matter that everyone stands behind their own name? Will it be centralized? Will it have sponsored posts? What will be the main type of content it offers?

If you have good ideas (and, of course, some fishing experience), now is exactly the right moment to turn them into a startup.

Science fiction writers have long been waiting impatiently for the moment when robots start to look like people. And with a little apprehension, ever since the days of their forerunner Frankenstein and the almost equally distant times of the Terminator.

That is why the news that, for the first time, a robot—the innocently smiling Ai-Da—dropped in for a chat with the British lords caught everyone's eye. Although her colleague Sophia has long been a star of the genre, having even been granted citizenship.

How far has technology come in creating the perfect humanoid robot? Is Ai-Da really so different that she can talk as an equal with the members of an almost thousand-year-old institution?

Is the time coming when we'll pass robots indistinguishable from ourselves in the street? Is it even possible? What are the biggest obstacles?

Between Ada and Ai-Da

And so, on October 11, 2022, a humanoid robot entered the House of Lords to have a chat with like-minded souls. No, not the way our friend Guy Fawkes did it, with barrels of gunpowder in the cellar, but through the main entrance. We don't know exactly how it got in, but the message of the visit was more interesting. What on earth did Ai-Da and the good old lords say to each other?

Let us introduce the charming guest. She is not only a robot but also a painter, a poet and a campaigner for the rights of artificial intelligence. Her name is a play on that of Ada Lovelace—the only daughter of Lord Byron, and one of the pioneers of the technologies that led to today's computers. Many consider her the first programmer in history, and a popular programming language bears her name.

The connection being sought is between art and robotics, between the human and the technological. It is no accident that Ai-Da was “born” of the meeting between Aidan Meller, a scholar of contemporary art, and a team of scientists from Oxford, who are in charge of the technological side.

RoBotticelli

Her main purpose, her creators say, is to provoke a conversation about how technology is changing art. Yes, we need such conversations more and more, and not only because of the enormous progress algorithms are showing in image generation, but also because of what is looming in more and more fields.

The painter has a three-dimensional camera in each eye, connected to a sophisticated computer vision system. Thanks to it, she registers the objects in front of her. And with her bionic hands she paints portraits, adding a moderate (and, as you can see, not always successful) dose of interpretation.

She already has quite a few successes in this line of work. She has painted Queen Elizabeth II and Billie Eilish, and has shown her work at the United Nations building and at the Venice Biennale. The New York Times calls her “a new voice in the art world,” while TIME magazine believes she “blurs the boundaries between machine and artist, an image from the future that suddenly becomes part of the present.”

In her spare time, the robotess writes poetry. She even reads other poets, polishing her style.

Ai, Da, If Only I Were a Rich Man's Child…

Despite her different “profession,” it was she, and not some robot built specifically for conversation, that the lords of the Communications and Digital Committee chose as their interlocutor. Obviously symbolic. And, incidentally, a sign of looking ahead, toward truly important questions that concern all of humanity. I have a hypothesis about why nothing of the kind has happened yet in the National Assembly, Bulgaria's parliament: after all, AI needs intelligent interlocutors.

Then again, against the backdrop of some recent British leaders, Ai-Da must have seemed a sensible conversation partner to Byron's colleagues (the lords, not the poets).

She appeared with an elegant fringe, a bright orange shirt and denim overalls. They asked her about the relationship between robots, AI and art, to which she replied timidly: “I do not have subjective experiences, although I can talk about where I am. I am dependent on computer programs and algorithms, which are very much not alive. But still, I can create art.”

From there she went on quite boldly. “The role of technology in creating art will continue to grow, and artists will find new ways to use it to express themselves, to reflect on and explore the relationship between technology, society and culture.”

Unpark Your Roboto. Lordo

“Nechem ti fordo” (dialect for “I don't want your Ford”)—you've surely heard this Bulgarian joke.

Yes, by tradition, when we see a new robot or algorithm, we first shower it with the eternal questions; nobody thinks of asking whether it fancies meatball soup for dinner.

This is where Baroness Stowell of Beeston, Tina Stowell, joined in. With the authority typical of her rank, she turned to the creators: “The robot is providing evidence, but it is not a witness in its own right. And I don't mean to offend the robot, but it does not occupy the same status as a human, and you, as its creator, are ultimately responsible for its statements.”

“Working on creating Ai-Da, I have learned a lot. And above all not about how human-like she can be, but about how much we ourselves have become robotic,” Meller replied aptly, hardly with the baroness in mind.

Not everything in the conversation went smoothly. At a certain point Ai-Da evidently got overexcited… and shut herself down. She had to be restarted, and in the meantime Meller put sunglasses on her, because “sometimes, while she's booting up, she pulls slightly strange faces.”

“Technology can be both a threat and an opportunity for artists,” the painter concluded her reflections.

Plenty to Chew On

As her website puts it, “if she is to do one important thing, it is to make us aware of how blurred the relationship between human and machine is becoming today. To encourage us to think more carefully and slowly about the choices we make for our future—the messages of Orwell and Huxley still ring true, and we would do well to be careful.”

Indeed, we can say that she gives us plenty to think about. For example, how much sense it makes to lay claim to human-like robots when we are obviously far from them. And is there any point in creating them at all? What does it give us and what does it take away if they visually resemble humans? Or is it more honest that way than “hiding” the machines purely in algorithms? On the other side of the network…

For now, the subject of androids frightens more than it excites. Incidentally, neither Ai-Da nor her even more world-famous colleague of recent years, Sophia, are androids, but gynoids, because they resemble not a man but a woman.

And that gives us one more reason to stop and think—why is it so often a woman that we try to recreate? And not only with robots, but with their invisible relatives, the chatbots. Both Siri and Alexa fall, in the supposedly so outdated binary classification of the sexes, on the gentle (again, by the old definitions) side of the paradigm.

Robots with Gentle Names

It will hardly surprise you that the (sub)consciously sought association is one of reassurance, gentleness, empathy—something we could never achieve if, say, we robotized the classic Bulgarian from the meme. Not to mention how much more viscerally sinister child robots are; there, horror writers have outperformed the science fiction crowd.

It is no accident that the pioneer Sophia was designed so that her face recalls the classic image of Audrey Hepburn from Hollywood's golden age. Again seeking something familiar, associative, a symbol of fragility and gentleness. Holly Golightly.

And Sophia really was the trailblazer of the genre, the first to achieve a closer visual likeness combined with sufficient mechanical capabilities. Over the past few years she has toured the world, even visited Bulgaria and left with nothing missing. Quite a few people were lucky enough to enrich their lives with the experience of talking to a robot-human.

Sophia even became an official United Nations ambassador. She built up social skills, recognized human faces and tried to read our facial expressions and emotions.

She was even officially granted citizenship by Saudi Arabia! Well, after it later became clear what happens to some citizens of that country in its own consulates abroad, perhaps that turned out to be a risk factor for longevity.

Made of Clay

Nadine, by the Japanese company Kokoro, was made to resemble her own creator, Prof. Nadia Thalmann, as closely as possible. She works as a receptionist at an insurance company in Singapore.

Junko Chihira also comes from the Land of the Rising Sun, but is of the male “sex.” He works as a tour guide; apparently he needs a bit more authority.

There have been so many other more or less successful projects meant to resemble humans, both in the West and in the East. And yet, in recent years the trend seems to be to imitate the physical version of the human… but not too much. To create androids aimed at specific tasks that don't look too much like us.

The example of Elon Musk is telling. Before he took it upon himself to save the world's freedom of speech, one of the ventures he had bet on seriously was the Optimus robot. It is humanoid but, for instance, has no face. Its job is to do its job, and it simply uses the human form because that form is the most proven for what is expected of it.

Nerves of Steel

This direction will certainly develop in the coming years; Musk's nose is rarely wrong. Robots will increasingly help in manufacturing, and in more “human” activities too, such as caring for the elderly.

Xiaomi's CyberOne is another example—it also has no face, but it can move like a real person. It responds to 85 different environmental sounds and recognizes 45 human emotions. It can change the color of its face and even has something like a pulse in its “hand.” At the main demonstration, they showed it handing a flower to one of its bosses. It wasn't the most delicate touch, but nobody got hurt.

I wouldn't show it to my kids, given how the robot vacuum cleaner of the same brand affects them at home. Still, it could be quite useful (and so is the vacuum cleaner!). Handing out flowers may be of no use; as a species we can still manage that ourselves (when we remember).

If it turned out to be good at washing windows, that would probably be much better. Its price, however, is currently around $100,000.

Looks Don't Pay the Bills, Robot

I found a survey by futurism.com from a whole five years ago intriguing: in which decade will we be able to create a robot indistinguishable from a human? Twenty-seven percent bet on the 2030s, and over 60 percent are convinced it will be a fact before 2050. Only one respondent says we won't manage it until the 2080s, because we have far too many problems to solve.

“Among other things, to do it we need to build: a general, autonomous artificial intelligence that can solve all kinds of tasks, mechanisms that perfectly replicate human movement, artificial skin, eyes, hair, tongue, voice, lips…” she writes.

Ameca is one of the newest developments in this direction (is it just me, or does the name sound like a toilet paper brand?). It is described as “a half-impressive, half-terrifying robot with realistic facial expressions, designed to facilitate interaction between humans and robots.”

It has become especially effective this year, after being connected to GPT-3. The algorithm, a true breakthrough in the AI world, has taken chatbots to the next level—they are considerably more coherent and can hold an almost human conversation. (Then again, it's hard to have an entirely human conversation with everyone on the bus.)

Ameca receives a question, thinks it over (actually, during that time it's asking the cloud) and, if the internet isn't too slow, answers with the most human facial expressions possible.

Give Me Your Paw!

But, all in all… why do we need a robot-human indistinguishable from a human? Is this aimless ego? And if we succeed, doesn't the next paradigm follow—how it will change human relationships, for instance love and sex?

Isn't this the big question, and not only in robotics but also in what we call artificial intelligence? Will we imitate the human, or will we build something different that does the job for us? Or that takes our jobs?

It seems there are enough people on this earth to talk to without making iron ones too…

I will never tire of repeating it, but fascinating times are coming. And, often staring at the progress of AI, we push robotics into the background, where miracles are (and will be) happening too. Who would have guessed that today we would really have such good self-driving vacuum cleaners? What bigger things await us in automation?

About one thing Ai-Da (or perhaps her creator; sometimes the line blurs) is certainly right. Today there is a lot to think about regarding the relationship between human and machine. And it's good that we do. The sooner, the better.

– I read a wonderfully fresh story—that the idea for Dronamics was born while your brother was studying in the Netherlands. And you wondered… how to send him a tin of cheese. Is that really how it happened?

– That’s exactly how it was. I was visiting him and we were talking about the little drones Amazon was developing—how on earth would they reach homes in Sofia, past dangling internet cables, neighbors who open your mail, kids with slingshots, glassed-in balconies. A few months later we spoke on the phone and he asked me: “When are you coming to visit again, so you can bring me more cheese?” I couldn’t be bothered, so I cut him off the way an older brother cuts off a younger one: “Leave me alone.

You’re an engineer, aren’t you? Build a drone and I’ll send you some.

But don’t bug me, I won’t be coming anytime soon.”

Then we started thinking: “Okay, fine, Bulgaria is close to the Netherlands, but you’d need something that flies and can last around 2,000 kilometers. So it has to be a bit bigger. It definitely can’t run on batteries; it needs some kind of normal fuel.”

Around the same time I had just come back from a trip to India. My smartphone broke and I asked my hosts to help. They recommended a website—Flipkart, similar to Amazon but local. There are no addresses there, just a field for “nearby landmark,” and I had to pick a school that probably had 10,000 children. For one more dollar, delivery was next day. The guy came, sent a text message five minutes early and somehow found us. I was very impressed and told myself: yes, those little Amazon drones won’t work in Bulgaria, but they won’t work in India either. There, even the big brands need 11 days to get from one end of the country to the other. A different kind of delivery makes much more sense.

– Which is what Dronamics actually goes on to offer… When did things get serious?

– When the idea was born, we first discussed it with some of my brother’s professors—whether, if we built a machine the size of a two-seater plane, but without a cockpit and a whole bunch of parts that aren’t needed for cargo, it would be cheaper to produce. Was all of this achievable?

They encouraged us, and meanwhile I dug into the economics. I came across plenty of data on how urbanization is bleeding smaller towns dry. One World Bank study made a particular impression on me: if a developing country improves the state of its transport infrastructure, that has a bigger positive effect on its economy than any other measure or policy.

In other words, all those ideas—privatize, cut taxes—nothing has an effect like simply unclogging the arteries so that blood reaches even the smallest organ and it doesn’t wither. That encouraged us even more, because

the truth, when it comes to moving goods, is not inside the city,

where you have lots of couriers and a hunger for jobs; the problem that needs solving lies between cities.

– Today it’s believed that all your big competitors are years behind you. How did you end up in such a strong position? How come you have a stronger product than Amazon? Is it only because they headed in the wrong direction?

– Nationality played a big role.

If we’d been Americans from Stanford, we’d not only have raised much more funding, we’d also have had much more competition.

Aviation is a terribly hard business. A program for a new machine in this class can take as long as ten years. Certification for passenger transport is brutal, and for cargo there wasn’t even a regulatory framework.

At some point all the big companies took wrong turns. They thought the last mile of delivery was the most expensive and that it was important to develop that. A bit like with autonomous cars. Nobody says anymore that they’ll be here next year; people talk about five to ten years.

In aviation it’s supposedly simpler, you have lots of space. But when you’re small and take off vertically, you don’t have much thrust. Besides, if you’re in an urban environment, you have obstacles of every kind. Electricity and batteries haven’t grown much at all in capacity, and their supply chain is very unstable.

A while ago we announced a partnership with DHL. Two months later they shut down their own small-drone project—they had worked with universities in Germany and gone through four generations. An example of an organization that said: “This is a super-complicated problem, we can’t solve it, let’s look at something else.” Whereas the other big organization, Amazon, decided that it was a super-complicated problem but that until it succeeded it wouldn’t try anything else.

– So the competition has no way of catching up with you soon?

– There will certainly be competition. That’s why our ambition is to position ourselves as a logistics company, so that if someone does catch up with us technologically in the future, we can buy their machines too. But until that moment comes, we’ll put every resource we have into extending our lead.

Cargo is the most thankless industry imaginable, because it’s the most price-sensitive, and new technologies are by definition more expensive. That’s why it makes more financial sense for everyone to balance the value by building “passenger flying cars” and then ripping out the seats to put cargo in, rather than saying, like us: this aircraft is only for cargo, and that’s all we’ll build it for.

As the saying goes,

do today what others won’t, so that tomorrow you can do what others can’t.

That’s what we decided too: we can see this is the future, we’re hugely confident in it, and we don’t care about the others. And we found ourselves in the position of first player in the sector. Now the goal is to stay first.

– What are the next big steps?

– Our program of ground and flight tests continues, and once those are finished we’ll be able to start commercial operations. We’ve already announced manufacturing partners in Australia, we’re about to announce some in Europe, and we’re in negotiations with several more regions. We’re producing the first units in Bulgaria, but the idea is for other companies to manufacture locally while we are their sole operator. To grow from here as a logistics company and an airline.

The most important thing was to have a working prototype, because aviation is a very hard business with very thin margins. I think it was Richard Branson who said:

The easiest way to become a millionaire is to be a billionaire and own an airline.

– What are the biggest risks that things won’t work out from here on?

– The more we work, the more the risks shrink. The initial risk with startups is the team. We’ve managed to build a very solid team of 150 people, about 100 of whom are in Bulgaria. The product risk—whether the idea works at all—will very soon fall away; we’re very confident of that, because we’ve already been through a whole bunch of tests. There’s regulatory risk, which has already been resolved: for three months now we’ve had a license to operate in Europe.

Next comes market risk—whether the market wants the product at all. Right now we’re at the stage of collecting orders. Our customer buys a certain tonnage at a certain frequency on a certain route. And even with current pricing, which will improve significantly,

there’s far more demand than we can supply, which is why we need as many manufacturing partners as possible.

What mainly remains is operational risk, which arrives once commercial operations begin. Making sure we hit the targets we’ve set for flights.

– Is the idea to have regular flights, or dynamic ones only when a particular shipment is needed?

– We’ll start with regular flights at first. Otherwise a customer would have to buy a whole flight even to send 2 kilograms from Sofia to Varna. So we’re starting with a schedule, and in a year or two we’ll also be able to do more flights on demand.

– If everything goes as expected, isn’t there a risk of “overloading” the sky? Of starting to cause problems for civil aviation too?

– We don’t think so. People constantly say the skies are very crowded. Even before COVID, when aviation froze completely, there were about 100,000 flights a day around the world. And there are 2 billion cars on Earth! Even if just 10 percent of them travel every day, that’s 200 million cars moving on just one plane, and only along tiny little “hairs” of it—the roads.

Yes, they’re slower, moving at 80 km/h rather than 800, but the difference with the air, where you have countless planes, remains huge. One of the problems today is specific points—at a mega-airport like Atlanta, for example, you need slots. The other thing is that air traffic control isn’t automated; you always need a human in the loop.

Of all those 100,000 flights, more than 80 percent are commercial aviation, which flies mostly above 10,000 meters. A two-seater Cessna “climbs” no higher than 3,000 meters; above that you need oxygen. While we fly at most up to 7,000 meters, so we operate in one huge empty space.

On top of that, our business model is to land at smaller airports—in Haskovo, Targovishte, Burgas, Varna. If our destination is Frankfurt, we’ll land at some small airport there, not the international one. There’s lots and lots of room for more machines in the sky. As long as everything is automated, you can guarantee that reactions will be very fast.

– One operator will be able to control 12 “black swans” at once. How is that possible?

– Before we even started, we did careful research on this. It turned out that in the military sphere—at that point the only place with large drones—one operator can monitor and control up to 15 machines at once. And that’s in a military context, when they have to constantly watch what’s happening. Whereas in the cargo world you’re traveling from Sofia to Varna, you’ve set the coordinates. Everything is deterministic, you can program it and step in only if there’s some exception, if something out of the ordinary happens. So we’re only starting at 1:1, we’ll move on to 1:12, and later one operator will be able to control many more.

– Your drone is called the “Black Swan.” Isn’t a black swan something many people associate with something negative? A sudden event that changes things, but not in a particularly good direction…

– Yes, during the global financial crisis of 2008 there was a lot of talk about The Black Swan, Taleb’s book. But our inspiration came from elsewhere. In the Middle Ages it was something like the Bulgarian “when the wooden clogs bloom”—a way of saying something doesn’t exist, like “when pigs fly.”

Then, around 1700, sailors discovered black swans in New Zealand, and the meaning of the phrase in Western Europe changed.

Something everyone thinks is impossible turns out to exist.

We knew we were starting such a project from Bulgaria, where no aircraft had been built for 70 years, where there were no trained people and no established supply chain. That it would be very, very hard. We knew what an American startup would do—first put an autopilot on an existing plane to validate the model. But we saw that this had already been done back in 2010. It clearly doesn’t work, because you’re using very expensive machines built for people, not cargo—small, cramped, with high maintenance costs.

And we told ourselves: so we need to skate not to where the puck is now, but to where it will be later.

Our aircraft has to be cheap to build and cheap to operate,

just one of the two isn’t enough. We named it that to remind ourselves that what we’re doing is actually super hard. So the engineers wouldn’t despair on the tough days.

Today our aircraft burns under 7 liters of fuel per 100 kilometers, carries 350 kilograms on board and flies at almost 200 kilometers an hour. A “flying banicharka.” But we’re also lucky that the technologies we use couldn’t have been created until about ten years ago. Neither in terms of computing power nor materials. So we’re the first company in the world to take advantage of the most modern things in the industry.

– Usually, with startups, everything ends in an exit—either a sale or going public. What would make you sell the company?

– It’s hard for me to imagine such a scenario. We simply want to do this. Being bought isn’t the optimal plan; we’re more likely to list on an exchange, most probably in the U.S., since that’s the most dynamic market and the one with the highest valuations. The idea is for that to happen in three to five years, with my brother and me continuing to run the company. We’ve put in so much time, desire, energy and work—I don’t think there’s anything else at all we’d want to do.

– Is it hard for two brothers to work together?

– For us it’s useful. Our families are different, but we’re very, very close, we grew up together. We trust each other completely, and on the other hand—an incredible bonus in any partnership—our areas of expertise complement each other. From the very beginning we’ve had a well-established respect for each other’s field.

– You told each other you wouldn’t shave until your venture succeeded, since beards really annoy you and that would give you extra motivation. But what’s the criterion for success—when will you shave?

– When the big aircraft lands successfully for the first time. So we expect to shave before the end of the year. I can’t wait—this month marks eight years with beards…

– I hear your next idea is to look toward space…

– We’re building a business that is generative. Surely, if we manage to pull this off in such a hard sector, other horizons will open up too. Humanity will always want more, faster, farther, so space really is the next goal.

– I wish with all my heart that things turn out the way you imagine them, and I’d be glad to do another interview just about space.

And you yourself… what do you dream of?

– That in 2100, when they rank the most significant companies, we’re number one. The one that contributed the most with something positive. Not Tesla, not Apple, but us. Companies lasting a long time is not a given at all… but dreams have to be ambitious!

– Not long ago a guest gave me a formulation that struck me as very accurate. We tend to overestimate the short-term effect of technologies and underestimate the long-term one. Is there something like that when we start talking about artificial intelligence?

– There is probably such a tendency in the approach and in the popularization. But the serious problem is the widespread misunderstanding of what this type of technology actually is, which is why the subject gets overgrown with myths. The first very clear line of demarcation is that

today we have narrow artificial intelligence, which can solve one specific task.

Whatever the approach—machine learning, neural networks or training through semantic languages—a model is built and achieves better and better results.

What people project, on the other hand, and what they fear most, is an artificial intelligence that would be self-aware. One that would have consciousness, and not only consciousness as we know it, but one that reflects on experience in some real environment.

The reason for concern today should be that we cannot control many of the risks. Especially with neural networks, programmers cannot see what happens below the third layer. It is known that OpenAI has achieved a very serious breakthrough and will most likely announce it soon—the GPT-4 model. They keep launching a model, letting it be tested, and when they see something worrying, for example a very strongly pronounced bias, they stop it and change it. Huge teams work on this.

– Its predecessor, GPT-3, certainly attracted enormous attention, and it is impressive how fast development is moving in that direction. In your view, what are the main risks in this field that we as a society should think about in good time?

– The impossibility of sufficient control is a problem the professionals have to solve, if they can. I think that in the long run it won't be possible. The more advanced artificial intelligence becomes, the more it will take on the characteristics of a black box, which is what our brain is too. And not because we program it wrong or because programmers don't know how, but simply because it is an extremely complicated and complex system.

But what people actually underestimate, and what they need to build an adaptive response to, is that

there is no human sphere that will remain untouched by digital technologies driven by artificial intelligence.

My plea is always that it be considered separately, because the other technologies really do have all the parameters of technologies, whereas AI is developing in a direction in which we will have to think of it in entirely different categories, even as a separate entity.

From our birth to our death, every human field will be permeated by these technologies. Including purely biological processes and ones we are not used to thinking of as a business niche.

In its documents, the Chinese Communist Party talks about the production of people between 2030 and 2050.

And this is not science fiction or transhumanism, but a concept for developing synthetic biology assisted by artificial intelligence, which follows genome tracking and selects the best genome for a human being. Of course, this raises profound moral and ethical questions.

– And then comes the future of artificial wombs, which is also being discussed more and more seriously…

– Yes, such experiments are already being done with mice. Then we see on what massive scale the impact of AI is unfolding in education and health care. Kindle ran an experiment in which they connected their device to an AI-based platform.

We read the e-book, and it reads us.

From facial expressions, from eye movements, from concentration on certain content, a cognitive deconstruction is made of where we struggle, which text our brain finds incomprehensible. This can gather information and create a personalized approach to education, but on the other hand, a lot of very sensitive data gets collected this way.

Medicine and agriculture are, in my opinion, the fields AI is entering fastest and most successfully. Agriculture in particular offers far more opportunities, because the moral and ethical risks are absent.

The Dr. Watson platform diagnoses trivial illnesses, and during the pandemic it was used by people who had no access to human doctors. Telemedicine is advancing, along with all the wearable devices that collect data from us. They measure parameters such as sweat, saliva and blood pressure, and even analyze breath, which can provide information on more than 300 diseases. Cameras connected to AI can deconstruct an illness from the way we move or from our facial expressions. We could go on with the subjects of aging, longevity and immortality. But as Yuval Harari says, this makes it possible for us to be watched or hacked “under the skin.”

– But while immortality still sounds like a distant future in every one of its aspects, this spread of AI into more and more professions will fundamentally change the labor market. What do you expect most in that direction?

– I can't think of a profession that won't be affected. People don't see or feel the short-term effects, but the change is coming very quickly. It isn't even true that it is happening more slowly here in Bulgaria; business today is international. Last week I was at the chocolate factory in Svoge. The production line is fully robotized and is the fastest of its kind in the world: it makes 6,600 chocolates a minute. Some workers quit as early as the training session, because they are shocked by such close contact with the robots.

Automation, robotization and artificial intelligence will enter every single sphere, and I predict this will happen within five years. Then the big question, which already concerns governments, is how to strike a balance between existing professions, new technologies and preserving jobs and incomes. A solution will probably have to be sought in alternative incomes that don't come from labor. Yes, these new technologies create new opportunities and therefore new jobs, but those jobs are specialized, tied to very specific digital skills, at least at a basic level, which are seriously lacking in Bulgaria, and in Europe as well.

– So far we have talked only about narrow AI, which offers one specific solution. But what do things look like when we go further out in our predictions? Toward artificial general intelligence and even the notorious singularity…

– In my view, what we really should worry about is the creation of general AI, and after that of super AI. The difference between them is thin. Nick Bostrom says that the moment one appears, literally within the next hour there will be a superintelligence, because it will very quickly, exponentially, teach itself to surpass us many times over.

You know about the debate: others believe this will never happen, because the question of consciousness is key. Steven Pinker, Bill Gates's favorite scientist, says it can't happen. Yet according to Yuval Harari, it doesn't need the kind of consciousness we have. If we are talking about consciousness at all, and an anthropocentric one, similar to ours. Sufficient speed of the algorithms could lead to a new quality.

When I talk to your colleagues who work in AI, I ask them why the breakthroughs happen, for example with GPT-4 or China's multimodal AI. According to them, what helps is the ever larger base on which these systems can be trained. GPT-4 will be trained on 570 billion sentences. The more data there is, the more clusters of consciousness appear. In other words, we see that factors such as “quantity” and “speed” may turn out to be enough to simulate consciousness.

For me this is more of a hypothesis, but it seems to me that at some point

humanity and our development begin to adapt to technology, and not the other way around.

And this cognitive decline, this mediocrity, the twilight of expertise and of science, seems to me to be adapting to a kind of technologized and very sterile thinking. People look for shortcuts; in science these are called heuristics. When I'm a guest on television, in 10 minutes they ask me questions that would take 20 hours, and not everything can be digested and presented that way, so it becomes unscientific and devalued.

– So even when we are not talking about true consciousness, enough accumulation could resemble it and even surpass it?

– My thesis is that perhaps this general AI doesn't need to develop a consciousness like ours. Certain parameters such as speed and quantity, which stimulate associativity, will simply be enough to simulate such processes. In my view, it is more likely that such a general AI will appear, and that is exactly what should worry us.

Last year I took part in a UNESCO intergovernmental meeting on ethical frameworks for AI. What personally troubles me is, first, that politicians perceive all this simply as technology, as software, while it has long since gone beyond those boundaries. And second, they don't think of it as a technology in continuous development.

When we talk about narrow AI, we must always discuss the risks, but the opportunities are still far greater, because very important solutions are being found. The fears and concerns should come because of general AI, and they need to be discussed by developers and engineers, by philosophers, ethicists, psychologists, by every kind of social scientist. And then this should be explained to the people who make the decisions, to the politicians.

– That is one of the big themes of Digital Stories too. I have given the floor to people from completely different fields, such as a priest, a conductor, a photographer. And yet I constantly run into crude irony and skepticism on social media: utter nonsense, this is so far off, pure fantasy. What are the chances that we overestimate these technologies, that we ascribe more capabilities to them, to narrow as well as general AI?

– We couldn't possibly overestimate narrow AI. You mentioned a priest: in Japan there is already a temple where that function is performed by an AI-based robot. Germany carried out a project to complete Beethoven's Tenth Symphony. He left only sketches, and an AI-based platform was trained on the music of that era, not only Beethoven's but also that of his like-minded contemporaries. There is even speculation that Banksy is an AI, or at least a collaboration between an artist and an algorithm.

So we see that it is entering every kind of field: in the creative ones it is forming new niches, new types of art, and in medicine it can detect abnormalities at the micro level. Simply because we don't have the cognitive abilities to handle such a volume of information and to find patterns.

It is underestimated because people don't see the examples, or rather don't pay attention to them. They watch Hollywood movies, at most they talk to Siri or Alexa, but very soon they will start noticing more applications. As for general AI, Steven Pinker may well turn out to be right. We have no answer as to what our consciousness is, any more than the unconscious and the subconscious; it is not produced by the brain, that much is clear.

A well-known American scientist, Eric Drexler, says it is better to keep it at the level where it provides us with a set, a complex of services in every sphere, but doesn't develop further and doesn't switch between them. Although in my view what Google and China are doing now is already beyond that line.

The overestimation lies rather in looking for a resemblance to humans, but it is not long-term.

– Musk criticizes Google's approach, saying that giving an algorithm access to such volumes of information without sufficient control would be the end of us as a species. So he offers the other paradigm instead: connecting ourselves to computers through the Neuralink brain-computer interface. Isn't that the more sensible long-term solution?

– I follow Elon Musk, and he has evolved quite a lot in his views. From 2015 to 2018 he shared Stephen Hawking's fears and invested instead in the concept of open artificial intelligence, OpenAI, to which everyone could add content, so that AI would reflect the state of humanity, of communities, of societies. But it turned out that many chatbots actually display racism, fascism and other extreme manifestations, simply because the biases are contained there, and in concentrated form.

It seems to me, although he has never said so explicitly, that this was what led Musk to the idea that our brain must be connected to a cloud system or AI, and that this should be part of human enhancement. Experiments have been done with monkeys and pigs, and a robot has even been built to perform this operation on humans. It was explained in great detail that a specific spot on the human skull is opened, a small piece of brain tissue considered unnecessary, the size of a sugar cube, is cut out, and the device, which is about the size of a 50-stotinki coin, roughly a U.S. quarter, is implanted. What isn't said is that once implanted, it can be deactivated but not removed, because that carries risks for the brain.

In my opinion, the biggest challenge is respecting the laws of thermodynamics. Every device, including my computer right now, overheats. You know what happens to protein when it overheats—coagulation and death.

And if we go further, still not knowing what consciousness is and how it drives our acts of will, with such a device present in the distant future we won't know which is our own expression of will and which is a mechanism prompting our brain to do something.

– In this direction there is also a big psychological barrier we have to get past, and we may have to do it extremely fast.

– Not long ago I spoke with a professor from South Korea who wants to have a Neuralink implanted, because she says it's the only way for her to stay competitive. Otherwise she won't be attractive to students, she won't have the necessary knowledge, because she develops linearly while technology develops exponentially.

People are becoming disoriented, and technology contributes to that. Every day the world produces as much information as in the last 8,000 years before technology. But we have no time at all to reflect on it, to draw conclusions. There could also be a strong trend of humanity turning toward the sciences of mental health and self-improvement. But there will probably also be a very strong trend toward connecting with technology—technological absolutism, and the thing that will de facto turn us into cyborgs.

– Are there any meaningful models that could channel information more thoughtfully, so that we perceive what is happening more adequately? I mean some form of journalism that would get us out of our bubbles. That would professionally present the things that really matter, instead of the way we get informed closing in more and more on social media, getting distorted and oversimplified there. So that we don't skip all the huge subjects and problems you and I are discussing now, which few people care about.

– I would like that, but I suppose that

first we will reach some kind of information cataclysm, and only then will solutions be sought.

Following the trends at Netflix and Apple TV, they are pursuing personalized, individual content. Platforms are even being developed, based on AI, that profile the individual and provide specialized information according to personal interests.

So the idea of some kind of collective media will probably fall away or shrink, and we will simply tune our platform to whatever interests us. We may end up receiving information diametrically opposed to what concerns our neighbor, even though we live in the same physical reality.

In my view, this will intensify the phenomenon of “echo chambers,” which is produced by algorithms anyway. There is an idea to create an internet free from this, to switch the algorithms off, and it will probably come to that, although it would collide with the idea of censorship.

Yes, it will be a kind of censorship, but a censorship of censorship.

The metaverse, which I expect to explode in the next five years, to virtualize things and create a mixed reality, will distort matters even further.

Today we have no strongholds to hold on to. This disorientation will become dangerous; it will lead to social clashes. What's more, we see that actions don't matter—it is words and messages that have a very strong effect. They are consumed, and only a small part of social groups looks for words to be turned into actions.

Yes, in the end I think something different will have to prevail, because it will be impossible to live and govern in such an utterly disoriented world. The point is that there also have to be people who want it…

– I'll be glad if people like that are exactly the ones reading Digital Stories today. Thank you!

– As someone with serious experience in this field, how do you see the startup environment in Bulgaria? Is our country a good place for ambitious ventures like yours?

– If I had to put it in one word: yes, it's a good place. The good thing is that here, on the whole,

there is an attitude toward entrepreneurship, there is that kind of spirit.

It's very easy to set up a company, and the bureaucracy at the start is relatively light. There are good funding opportunities to match companies' needs and their stage of development. If you have a good idea, you get a real chance to get started.

There is talent, even though many people believe there are no people. That isn't true. There are people—we simply want more than we have. At the same time, the talent is there.

From there on, some things aren't especially easy. The legal framework isn't good enough when it comes to startups. You can't do things like stock options or different shareholder rights. These aren't big obstacles while you're at the idea stage, but when you have to build an organization, a business, and make it grow, at some point they force you to register a company somewhere else. As a concept, that has always annoyed me a great deal, but right now AMPECO's parent company is registered in the US, even though we don't have a single person there and we are an entirely Bulgarian company.

– I'm surprised by what you say, that there are actually enough skilled people. Everyone in the software industry complains that there aren't enough…

– There are never enough people anywhere. We talk to a lot of colleagues; if you ask a German startup, they'll tell you the same thing. Nowhere are there enough people in the IT sector. There's nothing specific to Bulgaria about it.

– How did you end up in this niche? I read that the idea was born after you tried to drive an electric car from Germany to Bulgaria and ran into enormous difficulties…

– To tell the truth, the trip was part of our research into the current state of the charging infrastructure and the problems facing people who buy an electric car.

We believe that one day we will all switch to electric cars. So we did this experiment to experience the difficulties firsthand before rolling up our sleeves to solve them. We gathered quite valuable firsthand experience, but we combined it with serious research into the problems in this field and into how we could solve them in a way that would let us do something truly meaningful.

– The answer turned out to be that there was no comprehensive infrastructure bringing together the management of charging stations. Is that right?

– The answer turned out to be that the cars and

the technology are very advanced and ready for the transition, but the infrastructure is not

ready for charging. Literally wherever you touch it, there's room for improvement. From how to find a charging station to how to use it. Whether there's any information at all about whether it's free, what power you can charge at, how you'll pay. We ran into all of these problems. From stations that didn't work, to ones that were occupied, to stations we simply didn't know how to activate.

At first we convinced ourselves that if there were so many problems to solve, there must also be great opportunities. We'd roll up our sleeves and solve them all. Our enthusiasm, of course, far outstripped our initial capabilities, and we had to focus on exactly what we could offer, so that our contribution would be significant but also achievable.

That's how we found our thing: building software that enables operators to solve their customers' problems in the best possible way. Software that lets them avoid all the inconveniences we ran into as users.

– Who are the operators, most often?

– In some markets, electric mobility is still not very developed, consumers are skeptical, and the vast majority of new cars aren't electric. There, the operators of public charging infrastructure appear first, and they build fast charging stations. The biggest prejudice today, which is no longer really justified, is: I'll buy an electric car and there'll be nowhere to charge it. When I head to the seaside, I'll have

to call roadside assistance, because nobody can pour me a jerrycan of electricity.

That worry disappears with the arrival of fast charging stations for intercity travel.

In markets where electric cars are becoming more mainstream, most charging stations are in places where cars sit parked: at work, at home, in the garage, outside the hotel. These are slow charging stations, and this infrastructure appears after the electric cars.

In Bulgaria, the first operator was Eldrive, and they started with public stations. We can expect that in the future, as more and more electric cars arrive, we'll see more and more operators focused on slow charging.

– Which is a good thing, because then the price drops dramatically too. I read that in England, with your app, people can track prices, and since the system sometimes has a surplus of electricity, prices can even be negative. People get paid to charge their electric car…

– Here's another myth with no basis. Electric cars are often seen as a big danger to the power grid, and we worry about what will happen when everyone plugs in their cars to charge. Will there be enough electricity, will fuses start blowing and transformers exploding.

The truth is that electric cars are a resource that can be used to balance and optimize the grid. With the right technologies to make that possible, of course. Part of what we do is precisely about managing power and balancing the grid. So in the end, electric cars will have a positive effect.

– Right now things look pretty rosy for you: you're growing very fast in a niche that is expanding at a dizzying pace worldwide…

– Every startup is a roller coaster. You climb up and then

you plunge down sharply. So that you can appreciate the next climb.

Yes, right now we're going up, and I hope we'll keep going before the next drop comes. But if we look at the bigger picture, things are developing extremely positively. The growth of the sector contributes to that too—it's developing very fast. That tailwind matters, but the fact is that we're growing faster than the sector.

– What does it look like when you feel you've started plunging down that roller coaster?

– For us, the start of the COVID crisis coincided with the moment our initial funding ran out. We had started with enough financial resources to get us to the point of having our first customers and raising the next round of money to keep going.

The arrival of the first lockdown in 2020 thwarted our plans. We made a tough decision: to act as we would have if we'd had more substantial funding. If it hadn't worked out, it would have sharply cut short the company's life.

We managed to get over that unpleasant moment. Of course, for many other sectors it was even harder, but our customers literally couldn't go out and install stations. It was hard for them to make decisions about software and platforms while their business wasn't running. Even so, we managed to convince them, get them to sign contracts, help us, and move forward.

– I imagine the sector will grow even faster because of the war. Because of the energy transformations the Western world is being forced into.

– It's hard to predict the war's impact in this respect. Many of the things happening today, had they happened five years earlier, would have severely slowed the development of electric mobility. The supply chains disrupted by COVID, the shortage of chips, of batteries. We'd had a steady trend of falling battery prices, and last year, for the first time, they started going up.

And yet the share of new electric cars keeps growing, and this transformation is happening despite things that not long ago would have been catastrophic.

The wheel has turned. There's no doubt that the future of mobility is electric.

– When do you think this trend will reach Bulgaria?

– Here the market is still heavily dominated by second-hand cars. That means we have to look at which car models between five and ten years old are bought most widely. Unfortunately, five years ago there wasn't much choice of electric cars. So things are happening with a delay, but I don't think it will be any longer than the usual dynamics of our market.

We're certainly moving much faster when it comes to infrastructure.

The ratio of charging stations to electric cars is one of the best in Europe.

That shows business initiative, since in Bulgaria it's mainly private companies that are building the charging infrastructure. The exceptions are Varna, the largest city on Bulgaria's Black Sea coast, and a handful of other municipalities that have one or two stations each. The main initiative is private, and it shows that this is the future—and that it isn't coming in ten years, but much sooner.

– Do you have direct competitors globally?

– Even when we started, there were several companies building a very serious product we had to compete with. Lately I've been thinking that if I'd known everything I know now, we wouldn't have been so bold. But in my view, every startup needs a certain dose of naivety.

So that you can be bold enough to stand up to what would otherwise be unequal competition. Which, in fact, is never quite so unequal. There are objective reasons why

a new company can develop faster, be more agile, and so be able to beat giants.

We didn't start out swimming in a blue ocean, as the saying goes, where we're the only fish—quite the opposite. From the very beginning we landed in a highly competitive environment, but at this stage I'd say we're the company with the most suitable product.

And if we're not yet the biggest company offering this kind of solution, it's only a matter of another year or two.

– I read that many of the technical decisions you make have no equivalent anywhere, simply because nobody has faced a similar problem before. There are obviously competitors, but little know-how. Is that really so?

– The know-how really is scarce, and having competitors doesn't help much. In many other fields, of course, you copy good ideas and build on them—many startups do exactly that. We, however, had nothing to borrow, and maybe that helped us avoid quite a few mistakes. But it's a challenge we overcame through a great many meetings before we started.

There was a big dose of experimentation and trial and error, but also a lot of research. Thanks to that, we now have the largest concentration of expertise in electric mobility in Eastern Europe. We have to be at the heart of everything, in many markets, across a wide variety of businesses. We have to be able to give everyone the strongest weapon, so they can fight for the leading position in their own market.

– On the software side, I was really struck by your model, in which you have no QA engineers—specialists who test the software—and no hierarchy with team leads. Based on my own experience, that sounds adventurous.

– It is adventurous, I admit. Each of these things is subject to change, because I believe there's a right organization for the right moment, for the specific stage of development. We've experimented this way, it has worked for us, but we'll probably change it one day.

That's at the heart of every fast-innovating, fast-changing company: experiment quickly, apply and change, and don't set anything in concrete. Having no QA specialists doesn't mean having no tests; it's mainly driven by our strong desire for programmers to be responsible for the quality of what they build and for having enough automated tests.

– What motivates programmers to work hard in this setup?

– I can't speak for them. My role has always been more about creating an environment where people feel good, can be creative, and can do their job. I think what we do matters a great deal. There aren't many companies in Bulgaria where you can work on something connected with electric mobility, and do it at a high level, with global reach and influence.

On the other hand, I think we work well both in purely technical and in organizational terms. The right attitude, the right intentions, and having things well organized have been there from the very beginning, and I think that's quite an important factor.

Part of our motivation is to develop not only the product, but also the organization and the people in it.

At some point our company will come to an end—it will go public or merge into a bigger one. For me it would be wonderful if, by then, it had constantly been producing people who are experts in what they do, but also in the sector as a whole. People who have seen the best practices, who have learned and grown, who have had the chance to experiment and give their best.

And who become the next stars of the other startups they'll go on to build.

– You said your top priority is creating a good working environment. What's the most important thing for having one?

– There's hardly a single most important factor. I've always believed that a person needs a certain freedom in what they do. And also to believe that it matters. If it doesn't, nobody would want to do it in the long run, whatever the temporary reward—high pay, good status or something else.

If what you do doesn't bring you meaning and purpose, sooner or later you lose your motivation.

Could the moment be approaching when little humans will emerge from artificial wombs? More and more research teams promise a breakthrough in a field that may turn out to be the answer to low birth rates in the Western world.

But are we ready for a time when parents can watch together as their baby grows in a high-tech incubator? Not just technologically, but emotionally…

Robot Mother

Few scientific disciplines have come as far over the past 40 years as reproductive medicine. If we go back a little further, about a century, we see that infant mortality was horrifying. Gradually things changed, and more children survived the critical months thanks to neonatology.

Then the very process of conception changed forever. In vitro fertilization gave a chance at life to many children who could not otherwise have been conceived. And then came surrogacy; it even turned out that a woman doesn't have to be pregnant to have a child of her own.

And yet the economically developed part of the world is melting away. For reasons that clearly have little to do with the technology of reproduction itself and have much deeper and broader roots, birth rates in developed countries are falling, and gradually the same is happening in other countries as they join the list.

Recently Elon Musk and Vitalik Buterin turned their attention to the subject, and media attention followed. There was talk that the trend might be reversed thanks to an expected breakthrough that would make pregnancy unnecessary.

Life Is a Miracle

Prenatal education is a fascinating subject. There is serious evidence that while a baby is in its mother's belly, it takes in a huge share of the information coming from outside, and that information shapes it as an individual. It learns the language its parents speak, it gets used to their voices…

Today quite a few children come out of a womb that is not their mother's. Surrogacy became possible shortly after it turned out that there was no problem with a baby being conceived in a test tube rather than in the usual way… I mean the stork, of course.

In Bulgaria surrogacy is banned, except on objective medical grounds. Among celebrities in the West and the East, however, it is common practice. Yes, the baby has a mom and a dad; it's simply born from another woman's womb.

In some countries it's a business: young women decide it's a sensible way to secure a decent income, and the law allows it.

Now that there are plenty of children whose mothers never carried them “in their belly”… the next step seems logical. Let's build an artificial womb.

The Night Gives Birth from a Dead Womb…

The other medical specialty involved, neonatology, is advancing quickly too. Today specialists manage to save premature babies weighing a few hundred grams, tiny people no bigger than a hand's span, who a few decades ago would have had no chance…

The questions are meeting their answers. By all appearances, technology will soon allow babies to grow in an artificial environment. The bigger problem seems to be this: are we psychologically ready for that moment? Will it be the factor that reverses the birth rate trend? And at what price?

The occasion for talking about this came from one of the most interesting figures of our time. On his beloved Twitter, Elon Musk regularly posts crude jokes or claims that suddenly send a company's stock soaring. And sometimes he simply shares his views on the future of humanity, with the typical self-assurance of a court of last resort.

One such day was January 20 of this year, when Musk sparked the debate about artificial wombs. It began with the observation that demographics are humanity's biggest problem, and that because of them there will soon be no people left to send into space. Musk cited forecasts according to which the Earth's population will grow until the middle of the century and by its end will fall back to current levels. Over that time, however, Europe, Japan and China will be left with drastically smaller populations.

The Stork Retires

Nobody can accuse him, at least, of not doing everything in his power. He has seven children and shows no sign of slowing down. But as Musk also told The Wall Street Journal: “I think one of the biggest risks to civilization is the low birth rate and the rapidly declining birth rate. And yet, so many people, including smart people, think that there are too many people in the world and think that the population is growing out of control. It's completely the opposite. Please look at the numbers—if people don't have more children, civilization is going to crumble, mark my words.”

Sahil Lavingia, founder of the e-commerce platform Gumroad, chimed in on Twitter. He mentioned artificial wombs as a possible solution to falling birth rates. Another familiar hero of Digital Stories joined the discussion, Ethereum's creator Vitalik Buterin, who noted that synthetic wombs would ease the heavy social burden of pregnancy and reduce inequality. Buterin attached a chart that clearly shows how pregnancy affects women's pay today.

The fact is indisputable. Even in the United States, which has long fought for gender equality, women earn on average 79 percent of what men take home. In Japan the figure is 73 percent. Plenty of studies show that the cause is the period of pregnancy, which is entirely logical. Everyone has seen examples of this around them.

Mama Robot

According to Anna Smajdor, a professor of bioethics, pregnancy is barbaric. “If there were any other condition that caused such problems, we would classify it as a very serious illness.” This, in her view, is precisely what gives scientists a moral imperative to keep working on ectogenesis, as the scientific field aimed at creating an artificial womb is also called.

Yes, you will rarely hear politicians talk about such things, because the very idea still seems too strange. And yet, if it comes true, it could solve serious social and medical problems.

We already understand conception outside the human body well enough, and we can also care for a baby born much earlier than expected. All that remains is “simply” to cover the period in between.

Of course, it's anything but simple, because the mother's womb is a perfect creation of nature, the one that allows us to be on this planet at all.

Many teams are actively working on the subject, and news comes from all corners of the world. And although the big step doesn't yet seem very close, there is no shortage of curious details.

Born to Run

By tradition, the first serious progress comes with lab animals. In March of last year, a team of Israeli scientists reported that they had kept mouse embryos alive in an artificial uterus for a full 11 days. That's more than half the gestation period of our squeaking friends, which lasts 20 days.

This year perhaps the most interesting news on the subject came from China. Scientists from the Suzhou Institute of Biomedical Engineering and Technology announced that they are working seriously on the endeavor.

Among the curious details of their project is the involvement of artificial intelligence. The idea is that in its early stages, the embryo needs constantly changing and ultra-precisely maintained conditions in order to develop. The first weeks, when we turn from a fertilized egg into an ever larger and more human-like being, are full of complex processes that require careful delivery of the right substances, exact temperature and all kinds of conditions.

This is where the artificial intelligence comes in, which the Chinese scientists are counting on to control the parameters. The machine has a “bandolier” of fine tubes that deliver the necessary substances, plus a special device for supplying oxygen. For now it, too, works with rodents, and it's hard to say how long it might take to get permission for trials with humans.

In its article on the subject, the South China Morning Post noted that “mass ‘production’ of babies in an artificial womb factory could help maintain population numbers in a country whose citizens are reluctant to have children.” But at the same time it asked: “What might the social and psychological consequences be?” Interestingly, despite the demographic problems looming ever larger in China, surrogacy is not permitted there either so far.

Both Father and Mother

A team from the Netherlands has also been working in this field for years. In 2019 the specialists predicted that the artificial womb would be a reality within a decade, by 2029.

How close the breakthrough is, it's hard to say. Both because of the technology and because of regulation.

Of course, the whole pregnancy doesn't necessarily have to take place in such “devices.” Research on the subject could also help save many more babies who come into the world so early that medicine so far has been powerless. Today the 24th week of pregnancy is considered the critical point that largely determines the chances of survival.

Work in this direction has been going on since the 1950s. A laboratory in Philadelphia experimenting with lambs has made serious progress. As we remember from good old Dolly the sheep, these animals are an important stage in scientific research.

It looks shocking the first time you see the artificial womb in which the bleating little creatures develop. They are removed by cesarean section shortly after the midpoint of pregnancy, at a stage equivalent to the critical human 23rd to 24th week. The placenta is replaced by an oxygenator connected to the umbilical cord. Nutrients are also delivered through it, and carbon dioxide is taken away.

In a word: inside something resembling a plastic bag, you can see a baby lamb growing. The neonatologists and zoologists working on the study say there has been serious progress that could be applied to humans as well.

Robot Midwives' Day

Many of the prejudices have a basis. For instance, the purely everyday risks. A great many of the curses with which we in the Balkans express our attitude toward the world—most of them involving someone's mother—will have to change their meaning. It becomes even less likely that we'll get a new Stoichkov, after Hristo Stoichkov, the Bulgarian football legend as famous for his foul mouth as for his goals.

But joking aside, it's important to keep the psychological consequences in mind. And even more so those that come with the possible next steps. It's wonderful that women will have much more time to work, time that today goes to pregnancy, but… then why not go straight to building robots to look after our children while we work?

The baby incubator may give women a chance to work much longer, but it will put those who decide to give birth to their children themselves at a serious disadvantage. Meanwhile the hot spot in the labor market will shift from pregnancy and childbirth to child-rearing. And in many countries maternity leave is already horrifyingly short.

And what about the benefits of breastfeeding in the first months of a baby's life?

The claim that the family is the basic cell of society may sound like a socialist-era slogan, but it is actually Aristotle's idea. And the family is also one of the most conservative elements of everything that makes us human. How will it fare in the future, when babies start emerging from artificial wombs? The answer is clearly not simple, but it is directly tied to our future as a species…