{"url": "https://www.youtube.com/watch?v=hb9JPW_DkpQ", "page_url": "https://www.youtube.com/watch?v=hb9JPW_DkpQ", "title": "DeepMind Chief Demis Hassabis Says Google\u2019s Still Winning AI Talent | Semafor Tech", "show_or_channel": "Semafor (Cannes Lions)", "date": null, "duration_s": 1745, "type": "interview", "speakers": ["Demis Hassabis", "Reed Albergotti"], "confidence": "high", "notes": "Cannes Lions on-stage interview, June 2026 (Semafor article 2026-06-23).", "people": ["demis-hassabis"], "id": "0000_semafor-cannes-lions-deepmind-chief-demis-hassabis-says-googl", "audio_duration_s": 1744.917375, "worker": "jc-w22", "transcribe_s": 78.4, "model": "large-v3", "segments": [{"start": 2.29, "end": 30.77, "text": "It's great to see you. Seems like we always talk where it's very cold or very hot. Today is very hot. So let's see if we can get through this without sweating. Demis, everyone right now is freaking out about AI. They're banning AI models in DC. A lot of the concern, though, is about these text-based models that can create software, find vulnerabilities in computers. I'm wondering if you think"}, {"start": 30.77, "end": 55.71, "text": "As a lot of people do, that the path to AGI runs through these models like Mythos that may soon be sort of self-improving. Or do you think that it still requires a multimodal approach a la what you're working on at Gemini? Well, there's a lot there to unpack just in that first question. I mean, first of all, with the things that we're seeing with cyber and Mythos and..."}, {"start": 55.71, "end": 84.34, "text": "I've been pretty vocal for a long while that as we get closer to AGI, and I think we're on the cusp of that now, I sort of said statements like we're in the foothills of the singularity, that we need a bit more systematic approach to, of course, there's amazing opportunities ahead. A lot of things you talked about in the introduction, solving all disease, finding new energy sources. These are the reasons that I've worked on AI my whole career. But there are also risks. And cyber is one."}, {"start": 84.34, "end": 113.68, "text": "But I'm actually, there are going to be even more serious things. That's just a kind of warning shot for humanity. And I hope we take it seriously. But there'll be bio, nuclear, other kinds of risks coming down the line, maybe in the next couple of years. And we've got to get ready for that. And I think we need a more systematic way to deal with the issues and maybe kind of a standards body that ideally would be international as well, that would help test the latest frontier systems to make sure they're robust and the guardrails are sufficient."}, {"start": 113.68, "end": 127.26, "text": "So that's on the one hand of what you just mentioned. In terms of the technical approaches to AGI, we've always had a kind of, you know, the broadest, I would say, and deepest research bench."}, {"start": 127.26, "end": 154.43, "text": "That's why over the last decade, I think a lot of maybe 90% or plus of the big breakthroughs in AI that underpin the modern AI industry came from Google Brain or DeepMind as we were as separate research entities and now together as Google DeepMind. From Transformers that underpins all large language models to AlphaGo and all the reinforcement learning pioneering that we did back then. So I think..."}, {"start": 154.43, "end": 162.1, "text": "Our approach has always been to bet on multiple things and push them as hard as possible. So obviously we have our scaling work."}, {"start": 162.1, "end": 191.44, "text": "Our own multimodal foundation models, Gemini, we're pushing hard on coding. But also we have our multimodal genitive media models like Omni and VO. And we think those are important to give these models understanding of the world around us, the context around us. And I think in the end, to have a full AGI system, you need to be able to also understand the physical world around you. And you definitely need that."}, {"start": 191.44, "end": 215.34, "text": "I'm going to take that as a no. Thank you. So when you started DeepMind, you were so far in the frontier. And when you joined Google, it just seemed like between DeepMind and Google, there was like almost all of the major talent in AI was under one."}, {"start": 215.34, "end": 242.77, "text": "Corporate roof. Now you have at least three major competitors on the frontier who are all vying for the top minds. And I'm wondering, do you think that DeepMind today still has the right talent to win the race to AGI? Yeah, I think there's a lot of talent movement between all the leading labs and we win our fair share of the top talent. But what I would say is that"}, {"start": 242.77, "end": 270.22, "text": "We have by far the biggest and broadest research bench of any of the labs out there, the leading labs out there. And we continue to put out the absolute frontier work, whether that's on the foundation models or these other models that eventually will feed into the foundation models, like our Omni and Veo models too. But it's a ferociously competitive"}, {"start": 270.22, "end": 283.78, "text": "There's a market out there right now, probably the most ferociously competitive there's ever been in the tech industry. And I think that was inevitable. When I look back on this, we started this back in 2010, where I started DeepMind."}, {"start": 283.78, "end": 306.82, "text": "Nobody was working on AI, definitely not in industry, but even in academia, it was, you know, it was basically sort of thought to be career suicide. Like, of course, we know AI doesn't work. You know, we tried it in the 90s, places like MIT, and it was a dead end, you know, and that was the prevailing view. But we just felt, a small band of us felt that."}, {"start": 306.82, "end": 336.19, "text": "That actually with the right ideas and using learning systems, reinforcement learning and betting on neural networks, that a lot of fast progress could be made. And we were right in the end. But it also meant that now the whole world in the last few years has woken up to the potential of AI. That every important company in the world is going to get involved in it. Yeah. So we're here at Cannes. We're at an advertising conference. There's a lot of people here who are extremely creative. And I'm sure a lot of them,"}, {"start": 336.19, "end": 361.07, "text": "You know, even here in the audience are using your video creation tools to create ads, to do other things in the creative arts. What can you do with these tools now that you couldn't do a year ago? Well, I mean, every, I would say every month, these tools and the underlying models are improving massively. And a year ago, I just think."}, {"start": 361.07, "end": 371.38, "text": "The biggest change, I would say, with our tools, like with our new Omni model and things like Nano Banana for images, is the ability to kind of live edit."}, {"start": 371.38, "end": 393.26, "text": "What the output is of the generative models. So I think that's become extremely useful for creators. So, you know, it's part of the creative process, obviously, is you generate the first idea, the first concept, but you like some of it, but not other parts of it. You don't want to have to regenerate the whole thing, which is where we were a year ago. You want to be able to describe in natural language, ideally."}, {"start": 393.26, "end": 415.87, "text": "As you would to a designer, like, okay, keep that part the same, but change this to something else. And then iterate that maybe hundreds of times till you get to the final polished version that you want. So I think that kind of fine-grained control has been a big change over the last year, as well as just general relentless quality improvements. Yeah. I mean, there's also..."}, {"start": 415.87, "end": 437.01, "text": "Even controversies within the ad industry where people try to figure out, are they using AI at all? Is this 100% human created and you should disclose this, etc. Do you think that's a conversation that's sort of temporary because we haven't adjusted yet to how AI is going to change creativity? Or do you think that that's here to stay, that there will always be that?"}, {"start": 437.01, "end": 462.1, "text": "Well, there's two different parts to it. For certain, we need to deal with misinformation and deep fakes. So that is something we were cognizant of years ago when we first started down building these generative models three, four years ago. We foresaw that we would be in a world where these systems would be really good. Obviously, that's what we were planning to do. And they would eventually be almost as photorealistic."}, {"start": 462.1, "end": 480.56, "text": "And so therefore, we would need a system, digital watermarking system, which we created called SynthID, that was robust, was sort of unhackable, and would be embedded imperceptibly in the image. So that, you know, anyone, or citizen, a journalist, or..."}, {"start": 480.56, "end": 508.3, "text": "Government could go and detect whether that image was generated by an AI or not. And all of the things that we've, all of our models that generate anything from music to images to videos come with synth ID embedded in it. And we've also open sourced it and given it to the rest of the industry to use. So a lot of our industry colleagues have now adopted that standard, OpenAI, NVIDIA, and many other big ones. So I hope..."}, {"start": 508.3, "end": 537.26, "text": "Eventually, I think that should become almost a regulation, really, of like, if you're creating generative media, then it should come with provenance detection. And obviously, that will also help with things like right holders and IP rights, too. So that can all be sort of connected together. As to whether it should be disclosed if you use AI for a piece of the work that you're doing, I'm not sure. I think that might be just an era in where, okay, we were using"}, {"start": 537.26, "end": 567.01, "text": "Photoshop or some other tool before. And now this is a more advanced tool, but it's just a tool for your own creativity. I'm not sure that needs to be disclosed in the sense that you're talking about, other than you should know that the output was synthetically generated. If you look at your career, creativity is this through line. I mean, you started out creating video games. You study this as a neuroscientist, the nature of creativity in the brain."}, {"start": 567.01, "end": 587.02, "text": "Even AlphaFold, I think you could think of as a very creative approach to science, right? Now we have all these tools. There are people who would say, well, this is going to make us less creative. We're now just asking a model to do what you slaved for years doing in your career. So how do you think about it? How is it going to change creativity?"}, {"start": 587.02, "end": 616.34, "text": "It's definitely going to change it, but I think what I'm seeing is a twofold change. One is it's democratizing some of the creative tools so more people can try this and try out their ideas relatively quickly and relatively easily. That's double-edged, though, because it also produces a lot more things that maybe are not very creatively valuable. But also, it means a lot more people can break into those industries. I think there's a sort of lower bar"}, {"start": 616.34, "end": 634.5, "text": "There's less gatekeeping. So that will probably mean new creators, professional creators find a path wherever they are in the world through using these tools. And then the other thing I'm seeing is on the professional side, and we work with many professional directors and amazing collaborators."}, {"start": 634.5, "end": 646.56, "text": "And we try and talk to them to design our tools to help enhance and empower their creative process and help them with their creative process. I think it's..."}, {"start": 646.56, "end": 675.86, "text": "It's going to be incredible. They can sort of do 10x more things than they used to be able to do, try out more stream ideas, iterate faster through. They all have way more ideas than they can ever produce in their lifetimes. And so these tools allow them to try out things in relatively inexpensive and quick ways. So I think for the professional, they're going to be able to iterate their way to much cooler things way more quickly."}, {"start": 675.86, "end": 688.75, "text": "Any new tool, if you use it in the wrong way, the internet's the same, computers are the same. If you use it in a lazy way, it kind of takes away from the creative process. But if you use it in an innovative way, it should add."}, {"start": 688.75, "end": 714.48, "text": "to the creative process. And I think it's going to take a while for the creative industries to figure out the best way to use these things. And I talked to my game designer friends, you know, in the games industry, they're very excited about these tools. But I still I would say at least the games industry, which is the creative industry I know best, that we're still yet to figure out the any deep ways, the deeper ways of using this, but it's very early."}, {"start": 714.48, "end": 744.32, "text": "You know, so the games industry using it for obvious things like to create some assets and some graphics and things like that. But can it change the nature of games and introduce whole new genres of games? That's what I think could be possible. Like it was in the 90s when I was working, started out in the games industry when graphics and AI first came on the scene for computer games. And it allowed us to make whole new types of game genres. That's what I hope to see these new tools spark."}, {"start": 744.32, "end": 773.07, "text": "Do you think there's a criticism that these were trained on the outputs of humans, right? Should there be some sort of auditability that lets people see, oh, this output used partially one of my creations and I should get compensated for that. Do you think that should happen? Well, maybe a new economic model is needed. And I think that the tech industry and the creative industry together need to work together. And that's what happened with streaming, which changed."}, {"start": 773.07, "end": 795.54, "text": "You know, music and things like YouTube and then Content ID and YouTube specifically and Spotify and other companies like that came up with new, really robust business models. So I think that that will probably be needed. But it's very difficult, as everyone in the creative industries know, like to specifically attribute this is 1% this and 5% this and 10% that."}, {"start": 795.54, "end": 807.92, "text": "It's going to be difficult to kind of agree on objectively what that is. And we, even as human creators, the things we create are the output of all of the..."}, {"start": 807.92, "end": 835.44, "text": "All of the experiences we've had and the things we've learned and exposed ourselves to other art forms and other creators and what they've created. And then we mix all of that with our own creativity to generate the new things. So in some sense, that's always been the creative process. But we'll have to see if probably new business models will be eventually reneeded. I hear this a lot from people that, you know,"}, {"start": 835.44, "end": 860.51, "text": "I'm okay with AI being used for science to cure disease, for instance, right? The stuff you're doing in isomorphic labs. Yeah. But I don't like the fact that it's recreating music or the work that a filmmaker might have done or maybe even an ad agency. But I wonder if there's a point to be made here about sort of cross-discipline capabilities, especially when it comes to AI, where, you know..."}, {"start": 860.51, "end": 888.22, "text": "On the one hand, over here, you might be working at Isomorphic on a virtual cell, which we can't do today, but maybe one day we'll be able to actually see how a cell works in real time. And over here, where you're creating these world-class video models that may one day be able to sort of analyze that virtual cell and potentially help cure disease, create new therapies. Do you sort of see that happening down the road? I mean, help us understand."}, {"start": 888.22, "end": 913.25, "text": "Yeah, so the whole thesis behind AGI as a term and our original goal at DeepMind at the very beginning was to create this general purpose intelligent system that could learn from almost any input and then generate useful insights or spot useful patterns and then output that in almost any way."}, {"start": 913.25, "end": 934.59, "text": "That's obviously how the human mind works. Look at modern civilization that we've created with our hunter-gatherer brains. It's pretty unbelievable if you think about how that happened. And that's really what we know as general intelligence. And that's what we tried to focus on from the beginning of DeepMind and now the whole AI field of systems that are general and that learn."}, {"start": 934.59, "end": 962.99, "text": "Rather than being hard coded, hard programmed with the answer, which is, you know, it's funny to think back now, but that's what the AI field used to do for the first 50, 60 years of AI as a field. Things like Deep Blue, the chess program, and so on. And so what that means is that some of these things are inseparable. So if you want a fully general system that understands the world around you and can, like, analyze scientific papers or scientific data, including, like, visual data, like..."}, {"start": 962.99, "end": 990.14, "text": "Pictures of cells or proteins or little molecules even, depending on the resolution of the imaging equipment. It's the same type of things, a capability that you need to analyze YouTube videos or just the general vision that's coming through a camera. So a lot of these capabilities are general purpose and you develop them for one thing."}, {"start": 990.14, "end": 1017.39, "text": "But really, that's just a means to an end for another thing. And you can see that with first sort of five, six, seven years of DeepMind, we were working on games and AI being good at games like Go and Atari games. And obviously, one reason I picked games is because I love games and I make games and I've always been involved in games. But the real reason was because they were challenging tasks that were the right level."}, {"start": 1017.39, "end": 1035.6, "text": "for the AI systems at the time. So they were never an end in themselves. They were a means to an end, which was to help give us quantifiable and achievable intermediate goals that were impressive and very hard to do, but just about within the realms of possibility. And that would then..."}, {"start": 1035.6, "end": 1063.52, "text": "We trusted that would be a ladder to get us to a research ladder that would get us to where we are today, which is having these systems that can then eventually do really amazing things in the real world and tackle real world problems like scientific problems, like protein folding with AlphaFold and now drug discovery. And that's personally what I spend my time using these AI systems for is AI for science. That's always been my..."}, {"start": 1063.52, "end": 1088.93, "text": "It's fascinating how this is all connected. And I think back to your first paper as a neuroscientist, which is now famous."}, {"start": 1088.93, "end": 1118.59, "text": "In 2007, it tied the hippocampus and the brain to creativity. And it was this study of people who had lost their memory. And it found that people who had damaged the hippocampus and couldn't remember things also couldn't picture things, picture the future. And this visual aspect to creativity is so important. Like even fMRI studies on people who are blind from birth find that they access the visual part of their brain. So I'm just wondering, like, is that, do you think that,"}, {"start": 1118.59, "end": 1132.99, "text": "As you sort of try to recreate a machine hippocampus, so to speak, in AI that would let AI be creative, do you think that actually could come from, you know, just like training these models on the creative industries?"}, {"start": 1132.99, "end": 1156.5, "text": "Yeah, so as you mentioned, the through line between that was, so I first of all used my own visual creativity to help design and program these video games very early in my career. And then when I went into neuroscience to do my PhD, I was fascinated to try and uncover the mechanisms in our brain that allows us to do that, that all of us use all the time. It's at least the way I used to create."}, {"start": 1156.5, "end": 1166.24, "text": "For games was visualize the end goal, viscerally visualize a player, a kid playing the game and using the interface and thinking through even before it was."}, {"start": 1166.24, "end": 1195.54, "text": "It was there programmed, like what would be the issues with it and how would they find it fun and these types of things. And I kind of mentally simulated that. And we do that every day when we plan, you know, when we're going to have an important business dinner, say later, we imagine a lot of the times we sort of viscerally imagine, like, where's everyone going to sit? What am I, how am I going to open the conversation? You know, how are people going to feel about it? So we're using this sort of imaginative or future thinking is sometimes called capability."}, {"start": 1195.54, "end": 1220.32, "text": "And I had this suspicion when I first started my PhD, normally I was supposed to be doing it on memory, and memory had been studied for a long time, and memory is dependent on the hippocampus. And there are these rare patients that have had a disease that only just attacks the hippocampus, unfortunately for them, but leaves the rest of the brain intact."}, {"start": 1220.32, "end": 1250.11, "text": "And there's a few of them in the UK. We went to interview every single one of them. And I had this idea that reading all the memory literature, which is I did this sort of the first month of my PhD, was that there was two schools of thought. One is that it's a videotape and you just record everything that happens to you. And another, which obviously seemed wrong to me, and there was another school of thought, which is that it's a reconstructive process, that actually memory, when you remember something, you're actively reconstructing it from its past. And that seemed much more,"}, {"start": 1250.11, "end": 1254.74, "text": "Obviously correct to me, but if that was true, then imagination..."}, {"start": 1254.74, "end": 1282.13, "text": "Should use the same brain mechanisms. So it's just the goals different. Instead of trying to recreate something that seems familiar to you, this time you're trying to create something from those component parts that looks novel, that feels novel to your brain. And in fact, that's what we discovered. And we were the first people to, amazingly, to test any of patients on their imaginative capabilities rather than just their memory. Do you see any similarities between..."}, {"start": 1282.13, "end": 1288.22, "text": "What's happening under the hood with these video models recreating the world from prompts?"}, {"start": 1288.22, "end": 1314.64, "text": "And that and what's happening in the brain? I think definitely on a systems level. I don't know. I don't think the implementations are similar one to one. And that was never the idea behind doing neuroscience. It wasn't to copy the brain, but it was to understand the principles and the algorithms the brain might be using and the representations the brain was using and sort of lift that inspiration to then try and build that and into the direction of our AI models. So I think there are some."}, {"start": 1314.64, "end": 1343.62, "text": "For sure, some similarities between the way our new Omni models and VO models are generating the world. And there's definitely some things to be learned about, I think, how that system is working. And quite a few neuroscience professor friends of mine are actually indeed comparing the latest models about what they can do with a certain prompt with what a human might do in an fMRI machine and what images they might create. They're doing all sorts of..."}, {"start": 1343.62, "end": 1371.95, "text": "Crazy, amazing things like decoding what image the person's thinking about or dreaming about and then using one of these models to recreate actually the visuals and then asking the subject in the scanner, is that what you were imagining? And it is. So it's kind of, we're going to have these sort of amazing kind of sci-fi devices, I think, in the next few years. So interesting. You've talked about the Einstein test. I love this idea that you could sort of"}, {"start": 1371.95, "end": 1399.04, "text": "Give an AI all the data that Einstein had and nothing more. In other words, like the cutoff date is whatever. 1901. 1901. Yeah. And then see if the AI model could do what Einstein did, which is to come up with the theory of relativity and all these other physics breakthroughs that we use today. So when you hear that, though, you could almost imagine like text models, but are you really kind of imagining a more visual process?"}, {"start": 1399.04, "end": 1426.61, "text": "Well, I think you, first of all, that's how I would define true creativity, and that was my test for that is, because people always ask, well, how do you define it, where you're not just extrapolating something that already is known, but you're actually coming up with a new hypothesis, a new scientific hypothesis about some part of reality that is genuinely novel, like Einstein most famously did in 1905 with his incredible set of experiments and papers. So it's interesting."}, {"start": 1426.61, "end": 1444.45, "text": "It could be that there's enough in language that that's enough to come up with some new theory that was sort of hidden, cross-connected with all of the text, if you could read it all and hold it all in mind. But Einstein himself used to daydream while he was a patent clerk in Switzerland."}, {"start": 1444.45, "end": 1463.79, "text": "And this is well documented. And dream of these sort of thought experiments of, you know, being on trains and then if you were traveling at the speed of light, what would it look like? And so he was using his visual imaginative apparatus to come up with these new theories. And then he had to prove mathematically."}, {"start": 1463.79, "end": 1492.5, "text": "I think you're going to need to access and at least understand, and certainly if you're going to propose new experiments or have to do new experiments in order to test your hypothesis to develop it further, so it's not just a theory, then I think you're going to need to have an understanding of the world of atoms, not just the world of bits or the world of logic. Yeah. Back in your video game days, you had this game, The Republic, The Revolution, at Elixir, which is the company you founded."}, {"start": 1492.5, "end": 1515.62, "text": "Game was actually kind of a failure, but it was this idea, it was too ambitious. You were trying to recreate this former Soviet republic and simulate the world in a sense, right? Yeah. It's amazing because I think... On a Pentium 2003, it was probably a little bit too ambitious. Right, right. There was not an H100. I've always lived 10 years ahead of my time, yeah. Right, right. Now you have access to, you know, I..."}, {"start": 1515.62, "end": 1537.94, "text": "Tens, hundreds of thousands of GPUs at your fingertips. And you're building these virtual worlds again. It's funny how it kind of comes full circle. But do you imagine that this is where inside these virtual worlds, obviously they're going to be useful for robotics, right? Like training these things to go upstairs or whatever."}, {"start": 1537.94, "end": 1557.49, "text": "You know, Einstein in this virtual world, a virtual Einstein wandering around at the patent office and daydreaming. Like, is that where it's going to happen? Well, the reason is, look, with Republic, we tried to simulate a whole country with 100,000 living, breathing people sort of going about their daily lives and all the politics of it."}, {"start": 1557.49, "end": 1585.39, "text": "You were supposed to create a revolution. So it was a pretty ambitious game that we had to write by hand. And what's amazing now, and it took years, but what's amazing now is that we might be close to this possibility of actually just sort of generating that with some of our systems. I don't think we're ready yet, but in two, three years' time, something close to that might be possible. And then we could realize maybe the full vision of what I was thinking about then."}, {"start": 1585.39, "end": 1610.03, "text": "The reason this is all important and why it's all connected is simulations and AI, I think, are fundamental and they're very closely related. So simulations are going to be useful. Basically, that's what imagination is. It's a type of simulation. The reason simulations are useful is it allows you to try out many things in theory and then select the best path."}, {"start": 1610.03, "end": 1631.57, "text": "That's what AlphaGo did when it tries to select the best Go move in the current position. It simulates tens of thousands of moves using Monte Carlo tree search in this case, uses the model of Go to kind of constrain that to only the useful paths, and then it evaluates at the end of those 20, 30 moves which one of those end positions is the most promising."}, {"start": 1631.57, "end": 1653.49, "text": "And then that's what guides its next move and allows it to be the world champion. But there are many areas of the world, robotics and assistance are just two things, and science even. But there are many areas of the world where we would love to, in my opinion, kind of be able to have many reruns of that problem. I'll give you an example, economics, right? So economics is..."}, {"start": 1653.49, "end": 1678.08, "text": "It would be great if it was more like a natural science. So at the moment, we put up and down interest rates by half a percent and then we see, did it cause a recession? Oh, whoops, maybe we shouldn't have done that. But it would be much better if we could simulate hundreds of thousands of trajectories from here, the economy, what it would do if you adjusted these big levers and then get some kind of statistical..."}, {"start": 1678.08, "end": 1701.2, "text": "aggregate of all of those accurate simulations and then make an informed much more rigorous scientific decision about what to do quickly but that's not possible in a lot of the social sciences because you can't rerun the experiment in a controlled way hundreds of times like you can with the natural sciences so I think simulations which are learned and and and then where AI is connected is"}, {"start": 1701.2, "end": 1730.03, "text": "You can hand code a simulation if you understand the underlying system well enough. But most of the time, the things we want to simulate, whether it's like weather models, like we have the world's best weather models, or it's economics model, we don't actually understand well enough how the system really works on a mathematical level. So then an AI system could learn it, that simulation from the data. So that's sort of the bigger goal, if you like, of what I'm trying to do."}, {"start": 1730.03, "end": 1744.53, "text": "I love how you've tied the creativity part of AI with the science. And I'm sure you've given this audience a lot of inspiration in their work. So thank you so much, Dennis. Great to talk with you. Great to talk. Thank you."}]}