Mustafa Suleyman went from growing up next to a prison to founding the world's leading AI company. Dropping out of Oxford to start a philanthropic endeavour because he thought it would be of more real-world value than a degree, he went on to co-found DeepMind, which has since been acquired by Google and is leading their AI effort. 
In 2016, DeepMind gained worldwide fame for programming the first AI program to defeat the world champion of Go, considered the most complicated game in the world and with infinitely more variables than chess. There is no better authority on the progress of AI and what it means for all of us. His new book, 'The Coming Wave,' is out on September 5th.
In this conversation Mustafa and Steven discuss topics, such as:

Emotional Responses to AI

Surprises of the Past Decade

Concerns and Fears

The Containment Challenge

AI's Physical Manifestations

Regulating AI

The Future of AI Containment

AI-Human Interactions

Quantum Computing and AI

Cybersecurity Challenges

Founding an AI Company

Government's Role in Regulation

Containing AI: Strategies and Approaches

Emotional Impact of AI

The Shift Towards AI Interactions

Guidance for Young Innovators

Success and Failure Scenarios

Continuation of the Conversation


You can purchase Mustafa’s book, ‘The Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma’, here: https://bit.ly/3P5kbuS

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Are you uncomfortable talking about this?

the billionaire founder of Google's AI technology.

He's played a key role in the development of AI from its first critical steps.

In 2020, I moved to work on Google's chatbot.

We can use them to turbocharge our knowledge unlike anything else.

Every organization is going to race to get their hands on intelligence.

And that's going to be incredibly disruptive.

This technology can be used to identify cancerous tumors as it can to identify a target on the battlefield.

A tiny group of people who wish to cause harm are going to have access to tools that can instantly destabilize our world.

That's the challenge, how to stop something that can cause harm or potentially kill.

Yet you chose to build a company in this space.

Because I want to design an AI that's on your side.

I honestly think that if we succeed, everything is a lot cheaper.

It's gonna power new forms of transportation, reduce the cost of healthcare.

The really painful answer to that question is that

I find it incredibly fascinating that when we look at the back end of Spotify and Apple and our audio channels, the majority of people that watch this podcast haven't yet hit the follow button or the subscribe button wherever you're listening to this.

If you could do me a huge favour and hit that subscribe button.

I will work tirelessly from now until forever to make this show better and better and better and better.

I can't tell you how much it helps when you hit that subscribe button.

The show gets bigger which means we can expand the production, bring in all the guests you want to see and continue to do in this thing we love.

If you could do me that small favour and hit the follow button wherever you're listening to this, that would mean the world to me.

That is the only favour I will ever ask you.

Everything that's going on with artificial intelligence now, and this new wave and all these terms like AGI, and I saw another term in your book called ACI, it's the first time I'd heard that term.

If you had to encapsulate how you feel emotionally about what's going on in this moment?

How would you do, what words would you use?

I would say in the past, it would have been petrified.

And I think that over time, as you really think through the consequences and the pros and cons and the trajectory that we're on, you adapt and you understand that actually there is something incredibly inevitable about this trajectory and that we have to wrap our arms around it and guide it and control it as a collective species, as humanity.

And I think the more you realize how much influence we collectively can have over this outcome, the more empowering it is.

Because on the face of it, this is really going to be the tool that helps us tackle all the challenges that we're facing as a species.

We need to grow food 100x cheaper than we currently do.

We need renewable energy to be ubiquitous and everywhere in our lives.

Everywhere you look in the next 50 years, we have to do more with less.

And there are very, very few proposals, let alone practical solutions for how we get there.

Training machines to help us as aides, scientific research partners, inventors, creators, is absolutely essential.

And so the upside is phenomenal, it's enormous.

But AI isn't just a thing, It's not an inevitable whole.

Its form, the exact way that it manifests and appears in our everyday lives and the way that it's governed and who it's owned by and how it's trained, that is a question that is up to us collectively as a species to figure out over the next decade.

Because if we don't embrace that challenge, then it happens to us.

And that's really what I have been wrestling with for 15 years of my career, is how to intervene in a way that this really does benefit everybody, and those benefits far, far outweigh the potential risks.

and over the course of the first few years our progress was fairly modest But quite quickly in sort of 2013, as the deep learning revolution began to take off, I could see glimmers of very early versions of AIs learning to do really clever things.

So for example, 1 of our big initial achievements was to teach an AI to play the Atari games.

So remember Space Invaders and Pong where you batter ball from left to right.

And we trained this initial AI to purely look at the raw pixels, screen by screen, flickering or moving in front of the AI, and then control the actions up, down, left, right, shoot or not.

And it got so good at learning to play this simple game simply through attaching a value between the reward, like it was getting score and taking an action, that it learned some really clever strategies to play the game really well, that us games players and humans hadn't really even noticed, at least people in the office hadn't noticed it.

And that was amazing to me because I was like, wow, this simple system that learns through a set of stimuli plus a reward to take some actions can actually discover many strategies, clever tricks to play the game well that us humans haven't occurred to us, right?

And that to me is both thrilling because it presents the opportunity to invent new knowledge and advance our civilization.

But of course, in the same measure is also petrifying.

Was there a particular moment when you were at DeepMind where you go, where you had that kind of eureka moment, like a day when something happened and it caused that epiphany, I guess?

Yeah, it was actually a moment even before

where I remember standing in the office and watching a very early prototype of 1 of these image recognition, image generation models that was trained to generate new handwritten black and white digits.

So imagine 0 to 123456789, all in different style of handwriting on a tiny grid of like 300 pixels by 300 pixels in black and white.

And we were trying to train the AI to generate a new version of 1 of those digits a number 7 in a new handwriting.

Sounds so simplistic today given the incredible photo realistic images that are being generated.

And I just remember so clearly it, it took sort of 10 or 15 seconds and it just resolved it, that the number appeared, it went from complete black to like slowly gray.

And then suddenly these were like white pixels appeared out of the, the black darkness and it revealed a number 7.

And that sounds so simplistic in hindsight, But it was amazing.

I was like, wow, the model kind of understands the representation of a 7 well enough to generate a new example of a number 7, an image of a number 7.

And you roll forward 10 years, and our predictions were correct.

In fact, it was quite predictable in hindsight, the trajectory that we were on.

More compute plus vast amounts of data has enabled us within a decade to go from predicting black and white digits, generating new versions of those images, to now generating unbelievable photorealistic, not just images, but videos, novel videos, with a simple natural language instruction or a prompt.

You said you refer to that as predictable, but what has surprised you about what's happened over the last decade?

So I think what was predictable to me back then was the generation of images and of audio.

Because the structure of an image is locally contained.

So pixels that are near 1 another create straight lines and edges and corners, and then eventually they create eyebrows and noses and eyes and faces and entire scenes.

And I could just intuitively, in a very simplistic way, I could get my head around the fact that, okay, well, we're predicting these number sevens.

You can imagine how you then can expand that out to entire images, maybe even to videos, maybe to audio, too.

What I said a couple of seconds ago is connected in phoneme space in the spectrogram.

But what was much more surprising to me was that those same methods for generation applied in the space of language.

You know, language seems like such a different abstract space of ideas.

When I say like the cat sat on the, most people would probably predict mat, right?

I mean, there's a gazillion possible next word predictions.

I just couldn't wrap my intuition around the idea that we would be able to create the incredible large language models that you see

Inflection, my new company, has an AI called PII, a PII.AI, which stands for personal intelligence.

It's as good as chat GPT, but much more emotional, empathetic, and kind.

So it's just super surprising to me that just growing the size of these large language models, as we have done, by 10X every single year for the last 10 years, we've been able to produce this.

And that's just an amazingly large number.

If you just kind of pause for a moment to grapple with the numbers here, in 2013 when we trained the Atari AI that I mentioned to you at DeepMind, that used 2 petaflops of computation.

So peta, P-E-T-A, stands for a million billion calculations.

Yeah, just 2 of these units that are already really large.

And every year since then, we've 10x the number of calculations that can be done such that today, the biggest language model that we train at inflection uses 10 billion petaflops.

So 10 billion, million, billion calculations.

I mean, it's just unfathomably large number.

And what we've really observed is that scaling these models by 10x every single year produces this magical experience of talking to an AI that feels like you're talking to a human that is super knowledgeable and super smart.

There's so much that's happened in public conversation around AI, and there's so many questions that I have.

I've been speaking to a few people about artificial intelligence, try and understand it.

And I think where I am right now is I feel quite scared, but when I get scared, I don't get, it's not the type of scared that makes me anxious.

It's my very logical brain hasn't been able to figure out how the inevitable outcome that I've arrived at, which is that humans become the less dominant species on this planet, how that is to be avoided in any way.

The first chapter of your book, The Coming Wave, is titled appropriately to how I feel, Containment is Not Possible.

You say in that chapter, the widespread emotional reaction I was observing is something I've come to call the pessimism aversion trap.

Well, so all of us, me included, feel what you just described when you first get to grips with the idea of this new coming wave.

It's scary, it's petrifying, it's threatening.

Is my daughter or son gonna fall in love with it?

What does it mean to be human in a world where there's these other human-like things that aren't human?

And a lot of people over the last few years, I think things have changed in the last 6 months, I have to say.

But over the last few years, I would say the default reaction has been to avoid the pessimism and the fear, to just kind of recoil from it and pretend that it's either not happening or that it's all going to work out to be rosy, it's going to be fine, we don't have to worry about it.

People often say, well, we've always created new jobs.

We've only ever seen new jobs be created.

Unemployment is at an all time low, right?

So there's this default optimism bias that we have.

And I think it's less about a need for optimism and more about a fear of pessimism.

And so that trap, particularly in elite circles, means that often we aren't having the tough conversations that we need to have in order to respond to the coming wave.

Are you scared in part about having those tough conversations because of how it might be received?

So I've spent most of my career trying to put those tough questions on the policy table, right?

I've been raising these questions, the ethics of AI, safety and questions of containment for as long as I can remember with governments and civil societies and all the rest of it.

And so I've become used to talking about that.

And, you know, I think It's essential that we have the honest conversation because we can't let it happen to us.

Is, I mean, this is a big question, but As you sit here now, do you think that it is containable?

Where you give the example of how technologies are often invented for good reasons and for certain use cases like the hammer you know which is used you know maybe to build something but it also can be used to kill people and you say in history we haven't been able to ban a technology ever really It has always found a way into society because if other societies have an incentive to have it, even if we don't, and then we need it, like the nuclear bomb, because if they have it, then we don't, then we're at a disadvantage.

Honestly, I don't think an optimism or a pessimism frame is the right 1, because the both are equally biased in ways that I think distract us.

As I say in the book, on the face of it, it does look like containment isn't possible.

We haven't contained or permanently banned a technology of this type in the past.

So we banned CFCs, for example, because they were producing a hole in the ozone layer.

We've banned certain weapons, chemical and biological weapons, for example, or blinding lasers, believe it or not.

There are such things as lasers that will instantly blind you.

So we have stepped back from the frontier in some cases, but that's largely where there's either cheaper or equally effective alternatives that are quickly adopted.

In this case, these technologies are omni-use.

So the same core technology can be used to identify, you know, cancerous tumors in chest X-rays as it can to identify a target on the battlefield for an aerial strike.

So that mixed use or omni-use is gonna drive the proliferation because there's huge commercial incentives because it's gonna deliver a huge benefit and do a lot of good.

And that's the challenge that we have to figure out is how to stop something, which on the face of it is so good, but at the same time can be used in really bad ways too.

So I think that nation states remain the backbone of our civilization.

We have chosen to concentrate power in a single authority, the nation state, and we pay our taxes, and we've given the nation state a monopoly over the use of violence.

And now the nation state is going to have to update itself quickly to be able to contain this technology, because without that kind of essentially oversight, both of those of us who are making it, but also crucially of the open source, then it will proliferate and it will spread.

But regulation is still a real tool and we can use it and we must.

What does the world look like in, let's say 30 years, if that doesn't happen in your view?

People, because people, the average person can't really grapple their head around artificial intelligence when they think of it they think of like These large language models that you can chat to and ask it about your homework That's like the average person's understanding of artificial intelligence because that's all they've ever been exposed to of it.

You have a different view because of the work you spent the last decade doing.

So to try and give Dave, who's, I don't know, an Uber driver in Birmingham, an idea who's listening to this right now, what artificial intelligence is and its potential capabilities, if there's no containment, What does the world look like in 30 years?

So I think it's going to feel largely like another human.

So think about the things that you can do, not again in the physical world, but in the digital world.

I mean, more than that 2050, we will have new biological beings as well.

Because the same trajectory that we've been on with hardware and software is also gonna apply to the platform of biology.

No, I always look, I always use that as a cue for someone when a subject matter is uncomfortable.

And it's interesting, because I know you know so much more than me about this, and I know you've spent way more hours thinking off into the future about the consequences of this.

I mean, you've written a book about it, so, clearly you spent 10 years at the very deep mind as 1 of the pinnacle companies, the pioneers in this whole space.

And it's funny, because when I was, I watched an interview with Elon Musk and he was asked a question similar to this.

I know he speaks in certain tone of voice, but he said that he's almost, he's gotten to the point where he thinks he's living in suspended disbelief.

Where he thinks that if he spent too long thinking about it, he wouldn't understand the purpose of what he's doing right now.

And he says that it's more dangerous than nuclear weapons and that it's too late to stop it.

There's this 1 interview that's chilling and I was filming Dragons Den the other day and I showed the dragons the clip.

I was like, look what Elon Musk said when he was asked about what advice he should give to his children in a world of, in an inevitable world of artificial intelligence.

It's the first time I've seen Elon Musk stop for like 20 seconds and not know what to say.

Stumble, stumble, stumble, stumble, stumble.

And then conclude that he's living in suspended disbelief.

Yeah, I mean, I think it's a great phrase.

We have to, it's what I said to you about the pessimism version trap, we have to confront the probability of seriously dark outcomes.

And we have to spend time really thinking about those consequences, because the competitive nature of companies and of nation states is going to mean that every organization is going to race to get their hands on intelligence.

Intelligence is going to be a new form of capital, right?

Just as there was a grab for land or there's a grab for oil, there's a grab for anything that enables you to do more with less, faster, better, smarter, right?

And we can clearly see the predictable trajectory of the exponential improvements in these technologies.

And so we should expect that wherever there is power, there's now a new tool to amplify that power, accelerate that power, turbocharge it, right?

And, you know, in 2050, if you asked me to look out there, I mean, of course it makes me grimace.

That's why I was like, oh my God, it really does feel like a new species.

And that has to be brought under control.

We cannot allow ourselves to be dislodged from our position as the dominant species on this planet.

So these are sort of adjacent technologies that are rising with artificial intelligence robots.

You mentioned biological, new biological species.

Give me some light on what you mean by that.

Well, So, so far the dream of robotics hasn't really come to fruition, right?

I mean, we still have, the most we have now are sort of drones and a little bit of self-driving cars.

But that is broadly on the same trajectory as these other technologies.

And I think that over the next 30 years, we are gonna have humanoid robotics, we're gonna have physical tools within our everyday system that we can rely on, that will be pretty good, that will be pretty good to do many of the physical tasks.

And that's a little bit further out because I think there's a lot of tough problems there, but it's still coming in the same way.

And likewise with biology, we can now sequence a genome for a millionth of the cost of the first genome, which took place in 2000.

So 20-ish years ago, the cost has come down by a million times.

And we can now increasingly synthesize, that is create or manufacture new bits of DNA, which obviously give rise to life in every possible form.

And we're starting to engineer that DNA to either remove traits or capabilities that we don't like, or indeed to add new things that we want it to do.

We want, you know, fruit to last longer or we want meat to have higher protein, etc, etc.

Synthetic meat to have higher protein levels.

I think that the darkest scenario there is that people will experiment with pathogens, engineered, you know, synthetic pathogens that might end up accidentally or intentionally being more transmissible.

I, you know, they cause more harm or potentially kill.

And that's where we need containment, right?

We have to limit access to the tools and the know-how to carry out that kind of experimentation.

So 1 framework of thinking about this with respect to making containment possible is that we really are experimenting with dangerous materials.

And anthrax is not something that can be bought over the internet, that can be freely experimented with.

And likewise, the very best of these tools in a few years' time are going to be capable of creating, you know, new synthetic pandemic pathogens.

And so we have to restrict access to those things.

That means restricting access to the compute.

It means restricting access to the software that runs the models, to the cloud environments that provide APIs, provides you access to experiment with those things.

Of course, on the biology side, it means restricting access to some of the substances.

People are not going to like that claim because it means that those who want to do good with those tools, those who want to create a startup, the small guy, the little developer that struggles to comply with all the regulations, they're gonna be pissed off, understandably, right?

But that is the age we're in, deal with it.

That means that we have to approach this with the precautionary principle, right?

Never before in the invention of a technology or in the creation of a regulation have we proactively said, we need to go slowly.

We need to make sure that this first does no harm, the precautionary principle.

And that is just an unprecedented moment.

No other technology has done that, right?

Because I think we collectively in the industry, those of us who are closest to the work can see a place in 5 years or 10 years where it could get out of control and we have to get on top of it now and it's better to forego like that is give up some of those potential upsides or benefits until we can be more sure that it can be contained, that it can be controlled, that it always serves our collective interests.

So I think about what you've just said there about being able to create these pathogens, these diseases and viruses, et cetera, that could become weapons or whatever else.

But with artificial intelligence and the power of that intelligence with these pathogens, you could theoretically ask 1 of these systems to create a virus that a very deadly virus.

You could ask the artificial intelligence to create a very deadly virus that has certain properties, maybe even that mutates over time in a certain way, so it only kills a certain amount of people, kind of like a nuclear bomb of viruses that you could just pop, hit an enemy with.

Now, if I hear that and I go, okay, that's powerful, I would like 1 of those, there might be an adversary out there that goes, I would like 1 of those just in case America get out of hand.

And America's thinking, I want 1 of those in case Russia gets out of hand.

And so, okay, you might take a precautionary approach in the United States, but that's only gonna put you on the back foot when China or Russia or 1 of your adversaries accelerates forward in that path.

And this was the same with the nuclear bomb and, you know.

The idea that if I don't do it, the other party is gonna do it.

But the problem with that is that it creates a self-fulfilling prophecy.

So the default there is that we all end up doing it.

And that can't be right because there is a opportunity for massive cooperation here.

There's a shared that is between us and China and every other quote unquote, them or they or enemy that we want to create.

We've all got a shared interest in advancing the collective health and well being of humans and humanity.

See all The Diary Of A CEO with Steven Bartlett transcripts on Applepodcasts

Google DeepMind Co-founder: AI Could Release A Deadly Virus - It’s Getting More Threatening! Mustafa Suleyman