20VC: DeepMind's Demis Hassabis on Why AGI is Bigger than the Industrial Revolution | Why LLMs Will Not Commoditise & We Have Not Hit Scaling Laws | Bottlenecks in AI & The Energy Crisis Caused By AI | Whether AI Will Do More to Harm or Help Inequality

14:40Harry Stebbings:When we think about that future five years out, as you said, potentially with AGI, what does that world look like? Many people have different concerns. If we just start generally, what does that world look like to you?

14:52Demis Hassabis:I think on the positive side and the things obviously I've spent my whole career and life building towards AGI is I think it will be the ultimate tool for science and medicine. So in terms of advancing scientific discovery, finding cures to diseases, I think we need that kind of technology. And so I'm hoping in five years plus time we'll be sort of entering a new golden era, golden age of scientific discovery.

15:15Harry Stebbings:So my mother's got multiple cirrhosis. So it's like something that is the thing that I'm always most excited about. The thing I worry about is actually kind of drug discovery, the process of getting it through all the trials and knowing that it takes a decade before my mother will actually get any benefits from it. How do we solve that?

15:32Demis Hassabis:Yeah. So I think we'll get to that point soon. First of all, what we're doing is, you know, after we did the alpha fold project to do protein folding, then we spun out a company called Isomorphic Labs, which is doing extremely well. and that is supposed to, you know, the idea there is we're focusing on solving the rest of the drug discovery process, which is a lot of chemistry, designing the compounds, checking it's not toxic and all the different properties you need for drugs to be safe. I think we'll have that whole drug design engine ready in, you know, the next five plus five to 10 years. Then you're right.

16:03Demis Hassabis:The next problem is the clinical trials still take many, many years, right? But I think AI can help there in terms of simulating parts of the human metabolism, also stratifying patients to make sure that certain patients get exactly the right type of drug that's suitable for their genomic makeup. And so I think AI can help there too. But I think the real revolution will come when a few, maybe a dozen or so AI drugs get through the whole process. And then the government and the regulatory body see that and they have enough data to sort of back test the predictions of those models. And then maybe what we can do will be in the future where maybe 10 further years where we can really just trust the predictions that the models are making and actually then maybe skip out some steps, perhaps like the animal testing is not needed anymore.

16:50Demis Hassabis:Maybe we can go up the dosage ladder quicker because you can rely on these models. So I think we've got to do it in two steps, solve the drug design problem first, and then look at the regulatory length of time it takes.

17:02Harry Stebbings:Speaking of regulatory, AI safety is a big topic and a big concern. I think it was, again, I watched it last night over dinner, which was a great watch, which is obviously the documentary. And I think it was Stephen Hawking who said, we must get it right because we might not get another chance. Do you think that's right?

17:16Demis Hassabis:Yeah, I do think that's right. I think that is the stakes that we have to deal with. And there's two things I worry about. One is the misuse of these systems by bad actors and they can be repurposed. These are dual purpose technologies. They can be used for incredible good in science and health, as we just discussed, but they can also be repurposed for harmful ends by a bad actor. So that's one issue. Second issue is a technical one, making sure these systems, as they get more powerful, not today's systems, but maybe in a year or two's time when they become more agentic, more autonomous, as we get towards AGI, can they be kept on the guardrails that we want?

17:51Demis Hassabis:And I think regulation, the right kind of regulation could help here in terms of making sure there's at least sort of minimum standards from all of the leading providers. But it needs to ideally be a kind of international standards. What is the right kind of regulation?

18:07Harry Stebbings:And again, I'm kind of quoting yourself back from this documentary. You're like, I think we need more global coordination, which worries me because we're getting worse at it. Yes. Which I think would be an unwavering truth.

18:17Demis Hassabis:Yes, for sure. I mean, it's sort of crazy the timing that we're in, right, with this most consequential maybe technology the world's ever seen at the same time as a very fragmented sort of international system. And it's not ideal, but I think we're going to have to try and do the best we can to at least come up with a sort of set of maybe minimum standards, some benchmarks that test for undesirable properties, for example, deception. Nobody should be building systems that are capable of deception because then they could be getting around other safeguards. And then I imagine if things go well, some kind of certification process that basically it's almost like a kite mark of quality, that this model has certain safeguards and certain guarantees.

19:03Demis Hassabis:And so therefore, consumers and companies can safely sort of build on top of it. And I think that is how it should go, ideally. But it does have to be international, because of course, these systems are cross-border and they're cross-territory.

19:18Harry Stebbings:Who is that ultimate verification system? You obviously started with Theme Park.

19:22Demis Hassabis:Yes. A long time ago. Yes, brilliant. Don't put the burgers down too close to the roller coaster.

19:29Harry Stebbings:But, you know, obviously as a media company, I go through any media platform saying, I don't know what's real or fake. I'm always having to ask what's real or fake. Who is that arbiter of verification?

19:39Demis Hassabis:Yeah, well, I think there are, I mean, ultimately it's got to be government, I think. But, you know, the kinds of technical bodies that would be able to do the technical work would be like maybe the AI safety institutes. You know, there's a very good one in the UK that, you know, was set up under Prime Minister Sinek. and I think it's doing great work. And there's one in the US and maybe some of the leading countries that have the best research should also have an equivalent body that is staffed with high quality researchers too that can actually evaluate and audit these kinds of systems against certain benchmarks.

20:12Demis Hassabis:And I kind of like independently check whether they are meeting the right standards. If I could give you like a magic wand

20:19Harry Stebbings:that was only applicable to AI safety, sadly, What would be your implementation idea program that you would put in place with this magic wand?

20:27Demis Hassabis:Yeah, I think we need some kind of international body, maybe similar to the Atomic Agency, something like that, that perhaps the AI Safety Institute sort of feed into. And the research community has to also do this and be involved in like, what are the right set of benchmarks to check what types of traits, what types of capabilities? Maybe there are other safeguards too, like it wouldn't be desirable to have AI systems, output tokens that are not human readable. So in some kind of machine language that we couldn't understand, I think that would introduce a new vulnerability. So there's quite a few sort of things like that, which I think most of the leading labs would agree probably not best to do.

21:05Demis Hassabis:And then these bodies would, these institutions would test against those things. And I think that would give the public confidence and academia could be involved as well, as well as civil society, that these systems, which are going to get incredibly powerful, have been independently checked and audited. That's it. Your magic wand's done now. Yeah, sure. That was the one. Maybe I used it on the wrong thing.

21:26Harry Stebbings:Time will tell. Yes, exactly. You said that about science being one of the most exciting areas of 25 years of time. I have to ask it because it's one of the biggest concerns. It's the labour displacement problem. I just had Marc Andreessen on the show, actually, and he said that I was a Marxist.

21:41Demis Hassabis:I know, which I thought was like, it's a bit harsh. Yeah, Marc's wonderful.

21:46Harry Stebbings:So I'm not blaming him, but he was like, it's completely rubbish. I don't agree with that at all. We've always overcome it. How do you think about the labor displacement problem when you look at how truly capable these systems are? Yeah. And what that does to labor markets?

21:59Demis Hassabis:Well, certainly, you know, in the past, with every new revolutionary technology, there's been a lot of jobs disruption. So that's for sure. And I think that's definitely happened. So a lot of old jobs, you know, go away or not viable anymore. But then actually, the history of it is that a whole set of new jobs arrive that maybe one can't even imagine before. And those are higher quality, higher paying. So that's the normal course. Of course, you have to be very careful to say this time is different. And I guess that's what people like Mark are claiming is like, you know, it's the same as as as the last sort of, you know, 10 massive breakthroughs like the internet, mobile and so on.

22:33Demis Hassabis:I do think this is going to be bigger than all of those previous breakthroughs, technological breakthroughs. I mean, I sometimes quantify like AGI, the coming of AGI is like 10 times the industrial revolution at 10 times the speed. So unfolding over a decade instead of a century. You know, I've been reading a lot about the industrial revolution. There's a lot of great books about it that caused a huge amount of upheaval as well as a lot of advances. I mean, we wouldn't have modern medicine today. Child mortality was at 40 % back in pre-industrial revolution. So you wouldn't want it not to have happened.

23:06Demis Hassabis:But ideally, this time around, we mitigate some of the downsides a bit better than we did during the industrial revolution.

23:12Harry Stebbings:I often listen to amazing voices like yours. I get very excited by how fast it's coming. And then I try and stop myself from being too useful and think I should be more wise. And I'm told that we always overestimate what can be done in a year and underestimate what can be done in 10. Is that the truth here? Or is it actually coming faster than we know?

23:30Demis Hassabis:No, I think that's still the truth. I mean, maybe both timescales of short-term and long-term are nearer than other technologies. But I do think literally today, as of today and in the next year, things are a bit overhyped in AI. I mean, there couldn't be any more hyped in some ways. But on the other hand, interestingly, I still think it's still very underappreciated how revolutionary this is going to be in the sort of timescale of about 10 years. We could call that long-term. So there's still that dichotomy even today with AI. With the concern around labor markets, there's also a concern around income inequality and the concentration of wealth to few players.

24:07Harry Stebbings:How do you see that shaping out with the comment on the industrial revolution and what happens there?

24:13Demis Hassabis:Well, I think there's different ways that could play out. So, you know, maybe pension funds should be buying into all the big AI companies and making sure that everyone has a piece of that or sovereign funds. Maybe everyone, every country should have a sovereign wealth fund that does that. That would be the investment way of doing it. I think also there needs to be thought about if there is this massive productivity gain, but it's sort of narrow where that accrues, you know, how do we redistribute and how do we distribute that so that everyone benefits from these huge gains? And I can see all sorts of ways that could be done, including like providing sort of infrastructure and other things with that additional productivity gain.

24:51Demis Hassabis:I mean, there could be unbelievable things happening in the five to 10 year timescale, including like a breakthrough in some kind of renewable free energy. You know, maybe we solve fusion. We're working on that right with with with our partners at Commonwealth Fusion. I think AI is going to usher in, you know, maybe we have amazing new superconductors, better batteries, you know, material science. There's all sorts of ways I could see that completely changing the nature of the economy.

25:16Harry Stebbings:How do we solve the energy crisis that comes with an AI revolution? What it means in terms of energy requirements is unprecedented. I know it's an incredibly hard question, which I'm delving from really hard question to really hard. But how do we solve that unprecedented need for new energy?

25:29Demis Hassabis:Well, I think actually AI will in the medium to long run more than pay for itself, I think, in terms of energy costs. So, you know, we work on all these projects of like optimizing existing infrastructure, like optimizing the grid. I think we could probably get 30, 40 percent more efficiency out of our national grids. And then there's like modeling the climate and weather. And we have all sorts of the best kind of weather modeling systems in the world. So that helps us work out where the effects are really happening to mitigate that. And then finally, the most exciting maybe is like these new breakthrough technologies like fusion, like new batteries, superconductors that I think AI will be essential for helping us reach.

26:09Demis Hassabis:And then I think we'll be in a completely new energy situation than we've ever been as humanity where and then that will, of course, help with things like the climate and environment and eventually also help us get into space much more cheaply. Because if you have an incredible energy source like fusion, then you have effectively unlimited rocket fuel because you can just still catalyze seawater. I'm not going to ask you to solve space, don't worry. My question was on being in the UK.

26:39Harry Stebbings:You're in London. I'm in London. I'm very proud to be in the UK. You have been, I'm sure, pushed or prodded at every turn to move to the US. Why have you stayed?

26:48Demis Hassabis:Well, I should ask you that question too. But I think I saw in London when we started DeepMind as a place and the UK in general and Europe to some degree, there's incredible talent here. We've always had, I don't know what it is, three or four of the top 10 universities in the world with Cambridge and Oxford, Imperial, UCL, these kind of universities. So we're producing the envy of the world, really, these amazing graduates and PhD students. We have incredible scientists here. We've got rich heritage of that all the way from, you know, Turing and Hawking and Darwin, Newton. So, you know, we have this incredible history of scientific breakthroughs and having great thinkers.

27:27Demis Hassabis:So I felt we had all the ingredients and the talent and great engineers here, but it just hadn't been galvanized into an ambitious startup idea, deep tech startup idea. But I felt it was possible. And I felt that there was actually less competition here for that sort of talent. And we could even draw in the best talent from the top European universities. And that's what it was like in the early days of DeepMind. So I think it was a huge structural advantage for us. And then the final thing is maybe being a bit away from the valley, there is some disadvantage in that you're not plugged into the network and the gossip and the latest trends and vibes and all these things.

28:02Demis Hassabis:We're a little bit out of it here. But I think it's very conducive to thinking deeply about things, being more original about how you think. And I think that's great for things like deep tech, where, you know, you don't want to be distracted by the latest fad. You know it's going to be a 20-year mission, which is what we knew at the beginning of DeepMind. So I think being a little bit away from that maelstrom is quite good. I mean, Palmer Lucky at Angel often talks about being 400 miles away from the valley.

28:27Harry Stebbings:It's core to his kind of innovative thinking. Yes. We're a few thousand miles away, but yeah. Terrible question. Will Europe have a trillion dollar company? You see the Americans always bash us for our lack of large companies. I ping Daniel Ek and be like, come on, dude. Yes, exactly. But we don't have a trillion dollar company. Not yet.

28:43Demis Hassabis:I mean, Daniel might well get there with one of his companies, you know, Spotify, Helsing. I think those are two good options. I think there's no reason why we can't have that. I'm going to try and do that with Isomorphic, which is headquartered here and I think has the potential to be that. But that's one of the disadvantages of Europe is obviously we're a combination of smaller markets. So that's one thing we have to kind of overcome. Maybe this EU Inc. thing could be a good innovation. I'm pulling out the magic wand again. Yes. You can change one.

29:10Harry Stebbings:But this time applied to European technology. Yeah. What would you do to implement a growth mindset, a ability to build that trillion dollar company that we don't have to?

29:19Demis Hassabis:I think in the UK, I mean, this may apply to other European countries, too. I think unlocking what pension funds can invest in or just for the kind of growth stage. I think we're brilliant at doing the startup idea and getting it to a certain level like we did with DeepMind. But then if you really want to cross that sort of chasm into the trillion dollar global player, then where are the billion dollar rounds going to come from where you can really take on the existing incumbents? And I think that certainly was missing 10 years ago when I was doing fundraising for DeepMind. And I think it's still kind of missing today.

29:53Demis Hassabis:Just that kind of level of ambition and the amount the capital markets can support. I read about some of your early rounds raising in the Seb Maliby book.

30:01Harry Stebbings:Yes, it was quite hard work. Pitching families, kids. Yes, exactly. Exactly. Okay, we're going to do a quick fire round. So take me to meeting Elon for the first time. How was that?

30:10Demis Hassabis:Oh, yeah, it was amazing. It was at a founder's fund because we were both, SpaceX and DeepMind were part of a same portfolio, kind of amazing portfolio that Peter Thiel had at Founders Fund. I think we were both invited. I think I was invited to my first portfolio kind of conference. I think it must be back in 2011 or 2012, very early days. So we were the small little upcoming thing and I had a small speaking slot. And then Elon was the big thing in that portfolio. So he had the keynote. But then we met afterwards. I think it was in, Elon says it was like we were passing each other in the bathroom or something.

30:42Demis Hassabis:We said hi and we both hit off you know immediately like uh as sort of you know people that were almost too ambitious in their thinking perhaps and love sci-fi and and and i really wanted to visit his rocket factory so i was sort of trying to get an angular invite to to spacex and in la and i think i got there a couple you know he invited me at the end of that meeting and and that was our second meeting in

31:05Harry Stebbings:in the space effects factory i love it now i'm speaking slots as big as his yeah i don't know about that healthcare revolution disease eradication that you're most excited about again for me it's specifically with multiple cirrhosis yeah well look i want to literally

31:20Demis Hassabis:cure cancer i know people said that's the cliche but i actually what we're building at isomorphic is general purpose so we're trying to build a platform a drug design platform that will be applicable to any therapeutic area so ideally it will help with everything from neurodegeneration cardiovascular, immunology, cancer. Those are the ones we're focusing first, but eventually it should be applicable to every disease error. What are you thinking about that you're not reading about or seeing anyone talk about? So I think a lot of people are worrying about the economic questions around AGI. I worry a lot about the philosophical questions around it.

31:55Demis Hassabis:Like when it comes, let's assume we get the technical right. Let's assume we get the economics part of it right. Both of those are hard. Then there's a philosophical question of what is meaning, what is purpose we'll find out maybe what consciousness is what does it mean to be human i think that's what's coming down the road and i think we need some great new philosophers to help us to help us uh navigate that hard final question there are many different ways you could describe

32:18Harry Stebbings:what you do what would you most like to be remembered for your legacy to be i would like

32:24Demis Hassabis:my legacy to sort of be remembered for like advancing science building technologies that bring incredible benefits into the world, like curing terrible diseases. Thomas, thank you so much for putting up with my meandering conversation.

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