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Demis Hassabis reveals Google's three-stage stack rewrite: AI first, model first, agent first. Bolting agents onto normal software does not scale to billions. "We've got to, we've done a lot of engineering work under the hood in the last year, which you'll see, you see the surface of when... we announced things like this." "But actually, you can almost think that whole stack had to be rewritten to be sort of AI first, model first, and now agent first." "So that's quite a big change from like normal software." "And obviously there's all this huge infrastructure that serves billions of users every day at lightning speed and that's all gonna work." "And I think we've made massive improvements on that over the past year. And that's why you can see all the goodness of the AI models flowing through into our product surfaces so quickly and in such compelling ways." Most companies are adding an agent interface to yesterday's software. Demis says Google changed the substrate itself. The moat may not be the model. It may be the infrastructure that lets the model reach billions of users every day without breaking. - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind, with Rowan Cheung at Google I/O 2026show more

Karl Mehta

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Demis Hassabis reveals the 100,000-person synthetic country that took years to hand-code, and says AI may now generate it "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" "And 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" The leap is not better graphics. It is the cost curve of simulation: from years of hand-coding one world to asking a model to generate it. That turns synthetic societies from bespoke software projects into a reusable AI primitive. - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind, at Semafor Tech

Demis Hassabis reveals the 100,000-person synthetic country that took years to hand-code, and says AI may now generate it "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" "And 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" The leap is not better graphics. It is the cost curve of simulation: from years of hand-coding one world to asking a model to generate it. That turns synthetic societies from bespoke software projects into a reusable AI primitive. - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind, at Semafor Tech

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Demis Hassabis, Nobel laureate and CEO of Google DeepMind: "I think one day, maybe we can cure all disease with the help of AI. Within the next decade. I don't see why not." This is not a hype account. It is the man whose AI mapped 200 million protein structures in a single year, work that used to take a lifetime. A new drug normally takes ten years and billions of dollars. He thinks AI cuts that to months, maybe weeks. Musk said your future doctor will be AI. Hassabis is saying the disease itself might not be waiting for you by then. We treated illness as the fixed price of being alive. Two Nobel-level labs are now quietly saying that price was a choice.

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Demis Hassabis: AGI will be an intertwined model of Gemini, Genie and something like Nano Banana. Nano Banana shows first climps of AGI "It also has Gemini under the hood, it sort of understands what's going on semantically in those images, so I think that's sort of, it's getting towards a kind of AGIfor imaging" AGI will be the unification of the Genie 3, Nano Banana and Gemini models "And then eventually, we got to kind of converge all of those different projects. And they're intertwined. But we need to, you know, converge them all into one" Google seems to be doing everything right at the moment. With Genie 3, Gemini 3, and Nano Banana, they have all the prerequisites to create a general model that develops a true understanding of the real world.

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“Scientific progress is becoming computable.” DeepMind CEO Demis Hassabis says AI is becoming a scientific infrastructure layer, not just a productivity tool. At Google I/O, he introduced Gemini for Science: a new set of AI systems designed to help researchers read papers, write code, and generate hypotheses faster. The real shift is that research itself is starting to scale like software.

“Scientific progress is becoming computable.” DeepMind CEO Demis Hassabis says AI is becoming a scientific infrastructure layer, not just a productivity tool. At Google I/O, he introduced Gemini for Science: a new set of AI systems designed to help researchers read papers, write code, and generate hypotheses faster. The real shift is that research itself is starting to scale like software.

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DeepMind CEO Demis Hassabis says the AI bottleneck is already moving from model ideas to physical supply chains. "How much of the restriction at this point is physical? I am talking memory shortage, GPU shortage, and electricity." Demis: "That is constraining a lot of the deployment for sure. We see so much more demand for our models - Gemini and the other models that we have - than we can possibly serve." Then the less obvious part: "It does constrain a little bit the research, because you need a lot of chips to be able to experiment on new ideas at big enough scale that you can actually see if they are going to work." And on memory: "The whole supply chain is kind of strained... It still in the end actually comes down to a few suppliers of a few of the key components. Anywhere where there is some kind of constraint on the capacity, there is a sort of choke point." Important framing: The next AI race is not just who has the best model architecture. It is who can secure memory, chips, power, suppliers, and enough experimental capacity to find the next breakthrough before everyone else.

DeepMind CEO Demis Hassabis says the AI bottleneck is already moving from model ideas to physical supply chains. "How much of the restriction at this point is physical? I am talking memory shortage, GPU shortage, and electricity." Demis: "That is constraining a lot of the deployment for sure. We see so much more demand for our models - Gemini and the other models that we have - than we can possibly serve." Then the less obvious part: "It does constrain a little bit the research, because you need a lot of chips to be able to experiment on new ideas at big enough scale that you can actually see if they are going to work." And on memory: "The whole supply chain is kind of strained... It still in the end actually comes down to a few suppliers of a few of the key components. Anywhere where there is some kind of constraint on the capacity, there is a sort of choke point." Important framing: The next AI race is not just who has the best model architecture. It is who can secure memory, chips, power, suppliers, and enough experimental capacity to find the next breakthrough before everyone else.

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Demis Hassabis, CEO of Google DeepMind and Nobel laureate, says the AGI definition the industry uses is too low a bar. His Einstein test: train a system on a 1901 knowledge cutoff and ask it to invent special relativity. "The human brain is the only existence proof we have that general intelligence is even possible." "That's a pretty high bar, and it means that it's probably higher bar than just being able to do some useful economic work." "The type of test I would have is like an Einstein test of, you know, let's train one of these systems with a 1901 knowledge cutoff. Can it invent special relativity like Einstein did in 1905?" "What you'd actually want is something a future version of AlphaGo to be able to invent Go, right? Invent a game as deep and as complex and elegant and as beautiful as Go, not just come up with a strategy within the game." "I don't think today's systems are yet capable of doing that, but I think they will be able to in the future." - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind, on The Next Big Thing.

Demis Hassabis, CEO of Google DeepMind and Nobel laureate, says the AGI definition the industry uses is too low a bar. His Einstein test: train a system on a 1901 knowledge cutoff and ask it to invent special relativity. "The human brain is the only existence proof we have that general intelligence is even possible." "That's a pretty high bar, and it means that it's probably higher bar than just being able to do some useful economic work." "The type of test I would have is like an Einstein test of, you know, let's train one of these systems with a 1901 knowledge cutoff. Can it invent special relativity like Einstein did in 1905?" "What you'd actually want is something a future version of AlphaGo to be able to invent Go, right? Invent a game as deep and as complex and elegant and as beautiful as Go, not just come up with a strategy within the game." "I don't think today's systems are yet capable of doing that, but I think they will be able to in the future." - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind, on The Next Big Thing.

Karl Mehta

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Google just showed the part of the agent stack most people are still underestimating. Not the model. Not the chat UI. The memory substrate around the agent. In this Antigravity segment, Google describes an agent-first environment built around: - agent conversations - agent-produced artifacts - multi-agent orchestration - subagents - hooks - asynchronous task management That is not a nicer IDE. It is what happens when software stops being a sequence of chats and starts becoming a persistent workforce. Karl's article explains why the winning agents will not just be the ones with the smartest rented model. They will be the ones that remember what they did, what they learned, what changed, and what can be trusted. Full breakdown below.

Google just showed the part of the agent stack most people are still underestimating. Not the model. Not the chat UI. The memory substrate around the agent. In this Antigravity segment, Google describes an agent-first environment built around: - agent conversations - agent-produced artifacts - multi-agent orchestration - subagents - hooks - asynchronous task management That is not a nicer IDE. It is what happens when software stops being a sequence of chats and starts becoming a persistent workforce. Karl's article explains why the winning agents will not just be the ones with the smartest rented model. They will be the ones that remember what they did, what they learned, what changed, and what can be trusted. Full breakdown below.

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Anthropic CEO Dario Amodei : "Software is going to become cheap, maybe essentially free. The premise that you need to amortize a piece of software you build across millions of users, that may start to be false. But at the same time, there are whole jobs, whole careers that we've built for decades that may not be present. And, you know, I think we can deal with it. I think we can adjust to it. But I don't, I don't think there's an awareness at all of what, of what is coming here and the magnitude of it." --- From "The Wall Street Journal" YT channel (link in comment)

Anthropic CEO Dario Amodei : "Software is going to become cheap, maybe essentially free. The premise that you need to amortize a piece of software you build across millions of users, that may start to be false. But at the same time, there are whole jobs, whole careers that we've built for decades that may not be present. And, you know, I think we can deal with it. I think we can adjust to it. But I don't, I don't think there's an awareness at all of what, of what is coming here and the magnitude of it." --- From "The Wall Street Journal" YT channel (link in comment)

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Demis Hassabis explains Isomorphic Labs' 10x drug discovery engine, and why solving disease could also create a multi-hundred-billion-dollar business "If you ask me, the number one thing AI can do for humanity, it would be to solve hundreds of terrible diseases. I can't imagine a better use case for AI." "If you could revolutionize the drug discovery process, make it 10x faster and more efficient, and more likely to pass through the clinical trials because you can predict the properties better, that has to also be of enormous commercial value too." "I hope to do both with Isomorphic." "Build a multi-hundred-billion-dollar business. I think it has that potential, as well as being incredibly beneficial for society and humanity." The real health AI prize is not another chatbot. It is compressing the path from a predicted drug property to a clinical trial, then turning that speed into treatments for hundreds of diseases. Demis is making a rare dual bet: the most valuable AI company in biology may also deliver AI's most valuable public benefit. - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind and founder of Isomorphic Labs, on Bloomberg TV

Demis Hassabis explains Isomorphic Labs' 10x drug discovery engine, and why solving disease could also create a multi-hundred-billion-dollar business "If you ask me, the number one thing AI can do for humanity, it would be to solve hundreds of terrible diseases. I can't imagine a better use case for AI." "If you could revolutionize the drug discovery process, make it 10x faster and more efficient, and more likely to pass through the clinical trials because you can predict the properties better, that has to also be of enormous commercial value too." "I hope to do both with Isomorphic." "Build a multi-hundred-billion-dollar business. I think it has that potential, as well as being incredibly beneficial for society and humanity." The real health AI prize is not another chatbot. It is compressing the path from a predicted drug property to a clinical trial, then turning that speed into treatments for hundreds of diseases. Demis is making a rare dual bet: the most valuable AI company in biology may also deliver AI's most valuable public benefit. - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind and founder of Isomorphic Labs, on Bloomberg TV

Karl Mehta

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Demis Hassabis says he sold DeepMind in 2014 because staying independent needed $7 billion, and he could barely raise $10 million: "He saw Google as an AI company. The reason I sold was I knew it would require 7 billion dollars of investment in order to take on, try and become one of those companies." "And I was barely able to scrape together 10 million dollar rounds at that point." "And the problem was is that we'd done enough, the Atari thing, we had alerted enough of the Silicon Valley titans. They were coming after my people." "We had no business, we didn't even have a product, obviously not, because I was trying to make the core technology." "I was paying myself zero and people were being paid like 100k a year and then they were getting offers of 10 million a year." "And then if that didn't work, they could afford to come back and say, here's 50 million a year." "So at some point, that was going to go wrong." P.S: I'm hosting the AI Assurance & Governance Summit 2026 on October 1 at the Stanford Faculty Club, one day and one track, to work on the part of this that money did not solve. Frontier labs, regulated industries, insurers and investors in the room. Link in the reply. - Demis Hassabis (Demis Hassabis), co-founder and CEO of Google DeepMind, at the Worshipful Company of Information Technologists Annual Lecture.

Demis Hassabis says he sold DeepMind in 2014 because staying independent needed $7 billion, and he could barely raise $10 million: "He saw Google as an AI company. The reason I sold was I knew it would require 7 billion dollars of investment in order to take on, try and become one of those companies." "And I was barely able to scrape together 10 million dollar rounds at that point." "And the problem was is that we'd done enough, the Atari thing, we had alerted enough of the Silicon Valley titans. They were coming after my people." "We had no business, we didn't even have a product, obviously not, because I was trying to make the core technology." "I was paying myself zero and people were being paid like 100k a year and then they were getting offers of 10 million a year." "And then if that didn't work, they could afford to come back and say, here's 50 million a year." "So at some point, that was going to go wrong." P.S: I'm hosting the AI Assurance & Governance Summit 2026 on October 1 at the Stanford Faculty Club, one day and one track, to work on the part of this that money did not solve. Frontier labs, regulated industries, insurers and investors in the room. Link in the reply. - Demis Hassabis (Demis Hassabis), co-founder and CEO of Google DeepMind, at the Worshipful Company of Information Technologists Annual Lecture.

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Chamath: Tesla and Google are best positioned to win AI because they are building the full-stack Jason: "The game here is who wins the AI prize five years from now?" "Chamath, who's your number one and number two?" Chamath: " Tesla's one and Google's two." "And the reason is because they are the closest to having that vertically integrated stack that I spoke about." TESLA 1⃣ "I think that Tesla has the best vision models." "Now with xAI, they'll have one of the best LLMs and reasoning models." "And they'll be able to eventually stick that on Dojo." "And then all of that will be in all of the physical AI that you will interact with in your daily life." "Whether it's a robot, or whether it's a car, or whether it's a Robotaxi. So that's number one." GOOGLE 2⃣ "And then number two, for many of the same reasons, I think Google." "Because you'll have the Gemini family of models, which just absolutely kick ass." "Like Veo 3, which we haven't really spoke about, is gonna destroy Hollywood in the next year, like Hollywood is done, I think." "But they're landing model after model." "They have the TPU, and the next generation TPU I think is exceptional." "They're baking quantum." "And then they have an entire funnel of billions of people that they can direct experiences to." "So Tesla one, Google two."

Chamath: Tesla and Google are best positioned to win AI because they are building the full-stack Jason: "The game here is who wins the AI prize five years from now?" "Chamath, who's your number one and number two?" Chamath: " Tesla's one and Google's two." "And the reason is because they are the closest to having that vertically integrated stack that I spoke about." TESLA 1⃣ "I think that Tesla has the best vision models." "Now with xAI, they'll have one of the best LLMs and reasoning models." "And they'll be able to eventually stick that on Dojo." "And then all of that will be in all of the physical AI that you will interact with in your daily life." "Whether it's a robot, or whether it's a car, or whether it's a Robotaxi. So that's number one." GOOGLE 2⃣ "And then number two, for many of the same reasons, I think Google." "Because you'll have the Gemini family of models, which just absolutely kick ass." "Like Veo 3, which we haven't really spoke about, is gonna destroy Hollywood in the next year, like Hollywood is done, I think." "But they're landing model after model." "They have the TPU, and the next generation TPU I think is exceptional." "They're baking quantum." "And then they have an entire funnel of billions of people that they can direct experiences to." "So Tesla one, Google two."

The All-In Podcast

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Breaking: Google just launched Gemini 2.0, Project Astra, and AI agents for gaming & web browsing. I sat down with Demis Hassabis, CEO of Google DeepMind, to find out: (1:03) Everything launching and available to use today (2:13) The benchmarks/improvements of Gemini 2.0 (3:19) How close are we to an AI like in the movie 'Her'? (5:36) Will Project Astra be the first AI with infinite memory? (8:55) What's the ideal form factor for Project Astra? (10:34) What if people get too attached to their AI companions? (12:03) Is Demis creating an AI video game with Elon?

Breaking: Google just launched Gemini 2.0, Project Astra, and AI agents for gaming & web browsing. I sat down with Demis Hassabis, CEO of Google DeepMind, to find out: (1:03) Everything launching and available to use today (2:13) The benchmarks/improvements of Gemini 2.0 (3:19) How close are we to an AI like in the movie 'Her'? (5:36) Will Project Astra be the first AI with infinite memory? (8:55) What's the ideal form factor for Project Astra? (10:34) What if people get too attached to their AI companions? (12:03) Is Demis creating an AI video game with Elon?

Rowan Cheung

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Coinbase CEO Explains “Reverse Prompting” and the Rise of the AI CEO Brian Armstrong: “One of the big pushes we made in the last year was we got our own internal hosted AI model that was connected to all of our data sources, right?” “So it's like every Slack message, every Google doc, Salesforce data, Confluence, you know.” “So now the data is all aggregated and I've started to ask it really… it's not just like prompting it, ‘Hey, can you write this kind of memo for me,’ or something.” “I'm asking these AI agents now, ‘As CEO, what should I be aware of in the company that I might not be aware of?’ And it'll tell me, ‘Did you know that there's actually disagreement on this team about the strategy?’ And I was like, actually, I didn't know that.” “This is like reverse prompting. So instead of telling the AI agent what you want it to do, you ask it what you should be thinking more about.” @jason: “It's a mentor. It's a coach.” Brian: “Yeah. Like, what could make me a better CEO? And it's like, ‘Well, I looked at how you spent your time in the last quarter and here's how you said that you wanted to spend it, but you actually spent 32% of your time on this instead of 20%.’” “I've asked it other questions like, ‘What's the thing that I changed my mind on the most over the last year?’ Things like that.” “It'll prompt you with information you should be thinking about instead of the other way around.” Thanks to our partner for making this happen!: Our episode is sponsored by the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE 🏛.

Coinbase CEO Explains “Reverse Prompting” and the Rise of the AI CEO Brian Armstrong: “One of the big pushes we made in the last year was we got our own internal hosted AI model that was connected to all of our data sources, right?” “So it's like every Slack message, every Google doc, Salesforce data, Confluence, you know.” “So now the data is all aggregated and I've started to ask it really… it's not just like prompting it, ‘Hey, can you write this kind of memo for me,’ or something.” “I'm asking these AI agents now, ‘As CEO, what should I be aware of in the company that I might not be aware of?’ And it'll tell me, ‘Did you know that there's actually disagreement on this team about the strategy?’ And I was like, actually, I didn't know that.” “This is like reverse prompting. So instead of telling the AI agent what you want it to do, you ask it what you should be thinking more about.” @jason: “It's a mentor. It's a coach.” Brian: “Yeah. Like, what could make me a better CEO? And it's like, ‘Well, I looked at how you spent your time in the last quarter and here's how you said that you wanted to spend it, but you actually spent 32% of your time on this instead of 20%.’” “I've asked it other questions like, ‘What's the thing that I changed my mind on the most over the last year?’ Things like that.” “It'll prompt you with information you should be thinking about instead of the other way around.” Thanks to our partner for making this happen!: Our episode is sponsored by the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE 🏛.

The All-In Podcast

80,524 görüntüleme • 7 ay önce

Elon Musk on Grok: “I think an AI that is sort of SpaceX’s baby will be a very good AI. I think SpaceX is a collection of some of the very best humans on Earth, both in capability and morality and goodness, and I think we want to have an AI that is born of that capability and that morality and that goodness. I think that’s very, very important. So I’d like to encourage people to help out, actually, with the AI hardware on the ground and the AI software and, of course, with the AI satellites. Solar is going to be a very important part of that. The TerraFab will be a very important part of that, but we must also succeed on the software front, and we’re going to be training Grok on the sum total of all SpaceX information. So in a way, it will be trained on you. You will effectively be the parents of the AI. It will inherit your thoughts and ideas and beliefs, and I think that’s a good thing. So, yeah, we’ve got to win here on the AI hardware and the AI software. That maybe is the most important message. I think that is actually the most important message I wanted to convey today is that we must win on AI because the future is overwhelmingly AI and robots. So we won’t ultimately be able to control the AI. It’ll be too smart for that. But just like if you have a child that is a super genius child, you can still instill in that child the values and beliefs that you think are good and right. And so that’s why it’s incredibly important that we succeed with Grok. So, yeah, well, Grok 4.5 you’ve tried probably. We’ve got 4.6 coming out in about a week. And then 4.7 should be really pretty special. So I’d like to encourage everyone at SpaceX to use AI and to make it better.”

Elon Musk on Grok: “I think an AI that is sort of SpaceX’s baby will be a very good AI. I think SpaceX is a collection of some of the very best humans on Earth, both in capability and morality and goodness, and I think we want to have an AI that is born of that capability and that morality and that goodness. I think that’s very, very important. So I’d like to encourage people to help out, actually, with the AI hardware on the ground and the AI software and, of course, with the AI satellites. Solar is going to be a very important part of that. The TerraFab will be a very important part of that, but we must also succeed on the software front, and we’re going to be training Grok on the sum total of all SpaceX information. So in a way, it will be trained on you. You will effectively be the parents of the AI. It will inherit your thoughts and ideas and beliefs, and I think that’s a good thing. So, yeah, we’ve got to win here on the AI hardware and the AI software. That maybe is the most important message. I think that is actually the most important message I wanted to convey today is that we must win on AI because the future is overwhelmingly AI and robots. So we won’t ultimately be able to control the AI. It’ll be too smart for that. But just like if you have a child that is a super genius child, you can still instill in that child the values and beliefs that you think are good and right. And so that’s why it’s incredibly important that we succeed with Grok. So, yeah, well, Grok 4.5 you’ve tried probably. We’ve got 4.6 coming out in about a week. And then 4.7 should be really pretty special. So I’d like to encourage everyone at SpaceX to use AI and to make it better.”

DogeDesigner

64,434 görüntüleme • 1 ay önce

$Demis Hassabis, CEO of Google DeepMind, explains how young founders can build billion-dollar companies using AI tools the labs themselves haven't fully explored: He argues that the frontier of opportunity in AI is shifting away from building models and toward applying them. His advice to young founders: "You've got to just go with the flow of the direction. I would immerse myself in every tool available and just become almost like superpowered." Even at the frontier labs, the team can only scratch the surface of what's possible with their own technology. Demis Hassabis states: "So for us like Veo and Nano Banana and Gemini, even we can only explore a fraction of what the applied things you could do with it, the applications you could make with it." And the pace of new releases is making this even harder to keep up with: "I think that gap's getting bigger and bigger in terms of the overhang of the capabilities, all the cool stuff from the latest models, and the release schedules are getting faster and faster on that." This creates an enormous opening for outsiders willing to go deep on the tools. His conclusion is striking: "A kid these days could probably start a multi-billion dollar business in some ways using these tools in some new way that no one had thought about."$

Demis Hassabis, CEO of Google DeepMind, explains how young founders can build billion-dollar companies using AI tools the labs themselves haven't fully explored: He argues that the frontier of opportunity in AI is shifting away from building models and toward applying them. His advice to young founders: "You've got to just go with the flow of the direction. I would immerse myself in every tool available and just become almost like superpowered." Even at the frontier labs, the team can only scratch the surface of what's possible with their own technology. Demis Hassabis states: "So for us like Veo and Nano Banana and Gemini, even we can only explore a fraction of what the applied things you could do with it, the applications you could make with it." And the pace of new releases is making this even harder to keep up with: "I think that gap's getting bigger and bigger in terms of the overhang of the capabilities, all the cool stuff from the latest models, and the release schedules are getting faster and faster on that." This creates an enormous opening for outsiders willing to go deep on the tools. His conclusion is striking: "A kid these days could probably start a multi-billion dollar business in some ways using these tools in some new way that no one had thought about."

Big Brain AI

21,899 görüntüleme • 4 ay önce