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Demis Hassabis says that as we approach AGI, energy is effectively synonymous with intelligence AI will solve its own energy constraints by designing new materials, optimizing infrastructure and unlocking breakthroughs like nuclear fusion and room-temperature superconductors

Haider.

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79,708 просмотров • 6 месяцев назад •via X (Twitter)

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Demis Hassabis believes classical AI is enough for drug discovery, like AlphaFold has shown. But quantum computers may shine in material science, where data is scarce. They could simulate complex materials like superconductors or solar panels. DeepMind is actively exploring this frontier for breakthroughs in energy and tech. Quantum simulations might generate the missing data needed for major inventions.

Demis Hassabis believes classical AI is enough for drug discovery, like AlphaFold has shown. But quantum computers may shine in material science, where data is scarce. They could simulate complex materials like superconductors or solar panels. DeepMind is actively exploring this frontier for breakthroughs in energy and tech. Quantum simulations might generate the missing data needed for major inventions.

Wes Roth

53,450 просмотров • 6 месяцев назад

📁 Demis Hassabis says AGI could arrive in 10 years and usher in a new scientific era, but AI still lacks true creativity: it can’t, for example, devise on its own theories like Einstein’s special relativity in 1905.

📁 Demis Hassabis says AGI could arrive in 10 years and usher in a new scientific era, but AI still lacks true creativity: it can’t, for example, devise on its own theories like Einstein’s special relativity in 1905.

Jon Hernandez

31,435 просмотров • 10 месяцев назад

Demis Hassabis disagrees with Sam Altman’s idea that we’ve already passed AGI. He believes AGI has a clear scientific meaning—not just a buzzword. True AGI should match all human cognitive abilities, not just solve tasks. That includes creating new theories, making artistic breakthroughs, and inventing like Einstein or Mozart. Today’s models, in his view, are still far from that.

Demis Hassabis disagrees with Sam Altman’s idea that we’ve already passed AGI. He believes AGI has a clear scientific meaning—not just a buzzword. True AGI should match all human cognitive abilities, not just solve tasks. That includes creating new theories, making artistic breakthroughs, and inventing like Einstein or Mozart. Today’s models, in his view, are still far from that.

Wes Roth

19,640 просмотров • 6 месяцев назад

🚨 BREAKING: Google DeepMind CEO Demis Hassabis says AGI could arrive by 2030. And the impact will go far beyond software. Drug discovery could shrink from 10+ years to days AI may unlock entirely new scientific breakthroughs. At AI Ascent 2026, Demis Hassabis outlined what’s coming next: But he also made one thing clear: Today’s AI is still limited. And the next 1–2 years will be critical in shaping what happens next. The bigger shift: Watch the full talk below:

🚨 BREAKING: Google DeepMind CEO Demis Hassabis says AGI could arrive by 2030. And the impact will go far beyond software. Drug discovery could shrink from 10+ years to days AI may unlock entirely new scientific breakthroughs. At AI Ascent 2026, Demis Hassabis outlined what’s coming next: But he also made one thing clear: Today’s AI is still limited. And the next 1–2 years will be critical in shaping what happens next. The bigger shift: Watch the full talk below:

Atal

18,433 просмотров • 3 месяцев назад

Demis Hassabis says slow, scientific AI development was always the plan. “Everyone would be working on more narrow AI tools like AlphaFold.. curing cancer, helping with new materials.” But like coal powered the industrial revolution, the internet became AI's fuel source. Deployment scaled too fast, and we may not be ready for AGI.

Demis Hassabis says slow, scientific AI development was always the plan. “Everyone would be working on more narrow AI tools like AlphaFold.. curing cancer, helping with new materials.” But like coal powered the industrial revolution, the internet became AI's fuel source. Deployment scaled too fast, and we may not be ready for AGI.

vitrupo

48,350 просмотров • 1 год назад

Demis Hassabis says AGI is a scientific goal worth pursuing -- a testable frontier of general intelligence. Kate Crawford pushes back: the industry is already optimized for AGI. What it lacks is alignment with goals that serve people and the planet. "When do we build AI that's actually good for everyone? These are the real benchmarks."

Demis Hassabis says AGI is a scientific goal worth pursuing -- a testable frontier of general intelligence. Kate Crawford pushes back: the industry is already optimized for AGI. What it lacks is alignment with goals that serve people and the planet. "When do we build AI that's actually good for everyone? These are the real benchmarks."

vitrupo

29,243 просмотров • 1 год назад

Demis Hassabis says DeepMind is on track to solve intelligence by around 2030 As AI enters the "agentic era" of autonomy this year, the risk is that bad actors could repurpose the tech for harm "then we have to make sure... that these systems do what we expect them to do"

Demis Hassabis says DeepMind is on track to solve intelligence by around 2030 As AI enters the "agentic era" of autonomy this year, the risk is that bad actors could repurpose the tech for harm "then we have to make sure... that these systems do what we expect them to do"

Haider.

21,471 просмотров • 5 месяцев назад

Google DeepMind CEO Demis Hassabis said a new era of scientific discovery driven by artificial intelligence is on the horizon, with transformative impacts on medicine, energy and space exploration expected, but also warned of bad actors potentially misusing these systems

Google DeepMind CEO Demis Hassabis said a new era of scientific discovery driven by artificial intelligence is on the horizon, with transformative impacts on medicine, energy and space exploration expected, but also warned of bad actors potentially misusing these systems

Reuters

44,724 просмотров • 5 месяцев назад

🤔How do we envision the future? Our AI-generated video inspires limitless possibilities.📹 🆕With a focus on innovation, green development, digital intelligence and integration, we're driving momentum through "new energy, new infrastructure, new industry and new materials".💚

🤔How do we envision the future? Our AI-generated video inspires limitless possibilities.📹 🆕With a focus on innovation, green development, digital intelligence and integration, we're driving momentum through "new energy, new infrastructure, new industry and new materials".💚

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58,726 просмотров • 1 год назад

Demis Hassabis says we may not have enough time to prepare for AGI. Yet he helped accelerate the field by openly publishing breakthroughs like transformers and AlphaGo. What’s changed is asymmetry. A few labs give. Many others just take. “That’s a little bit unsustainable over the long term.”

Demis Hassabis says we may not have enough time to prepare for AGI. Yet he helped accelerate the field by openly publishing breakthroughs like transformers and AlphaGo. What’s changed is asymmetry. A few labs give. Many others just take. “That’s a little bit unsustainable over the long term.”

vitrupo

55,832 просмотров • 6 месяцев назад

The interview with Demis Hassabis - the tl;dr (summary) about scaling, AGI and much more: 1. Solving the "Root Node" Problems: DeepMind isn't just building chatbots; they are using AI to solve the hardest scientific problems. After the success of AlphaFold, they are now targeting materials science (room-temperature superconductors, better batteries) and even nuclear fusion to unlock unlimited clean energy. 2. The "Jagged Intelligence" Paradox: Current AI models are in a weird spot—they can win gold medals at the International Math Olympiad but still fail at basic logic puzzles. Hassabis calls this "jagged intelligence." The goal isn't just more data, but fixing these inconsistencies to make models reliable across the board. 3. Scaling is Not Dead (But it’s Changing): Despite rumors of hitting a "data wall," Hassabis says we haven't seen a hard limit yet. However, we are seeing diminishing returns. His bet? Getting to AGI will require 50% scaling and 50% architectural innovation. It’s no longer just about making the models bigger; it’s about making them smarter. 4. The Missing Piece: System 2 Thinking: Today's models are passive—they just spit out an answer. To reach AGI, we need systems that can "think" before they speak. This involves planning, reasoning, and double-checking their own work (similar to human "System 2" thinking) rather than just predicting the next word. 5. Rise of World Models: The next big frontier is "World Models" (like their project Genie). AI needs to understand the physics of the world—gravity, object permanence, and cause-and-effect—not just language. This is crucial for building helpful digital agents and robots that can navigate real-life situations. 6. Is the Universe Computable? On a philosophical level, Hassabis believes that everything in the universe might be computable. His life's work is testing the limits of the "Turing Machine." If we can build an AGI that simulates the human mind perfectly, we might finally understand what (if anything) makes human consciousness unique. 7. Bigger than the Industrial Revolution: We need to prepare for a shift that is 10x faster and bigger than the Industrial Revolution. If AI solves energy (fusion) and labor, we might enter a "post-scarcity" world. Hassabis warns that society, economics, and governments need to adapt quickly to ensure these benefits are shared by everyone, not just a few. And since this is the most important aspect, here is the clip about post labor economy:

The interview with Demis Hassabis - the tl;dr (summary) about scaling, AGI and much more: 1. Solving the "Root Node" Problems: DeepMind isn't just building chatbots; they are using AI to solve the hardest scientific problems. After the success of AlphaFold, they are now targeting materials science (room-temperature superconductors, better batteries) and even nuclear fusion to unlock unlimited clean energy. 2. The "Jagged Intelligence" Paradox: Current AI models are in a weird spot—they can win gold medals at the International Math Olympiad but still fail at basic logic puzzles. Hassabis calls this "jagged intelligence." The goal isn't just more data, but fixing these inconsistencies to make models reliable across the board. 3. Scaling is Not Dead (But it’s Changing): Despite rumors of hitting a "data wall," Hassabis says we haven't seen a hard limit yet. However, we are seeing diminishing returns. His bet? Getting to AGI will require 50% scaling and 50% architectural innovation. It’s no longer just about making the models bigger; it’s about making them smarter. 4. The Missing Piece: System 2 Thinking: Today's models are passive—they just spit out an answer. To reach AGI, we need systems that can "think" before they speak. This involves planning, reasoning, and double-checking their own work (similar to human "System 2" thinking) rather than just predicting the next word. 5. Rise of World Models: The next big frontier is "World Models" (like their project Genie). AI needs to understand the physics of the world—gravity, object permanence, and cause-and-effect—not just language. This is crucial for building helpful digital agents and robots that can navigate real-life situations. 6. Is the Universe Computable? On a philosophical level, Hassabis believes that everything in the universe might be computable. His life's work is testing the limits of the "Turing Machine." If we can build an AGI that simulates the human mind perfectly, we might finally understand what (if anything) makes human consciousness unique. 7. Bigger than the Industrial Revolution: We need to prepare for a shift that is 10x faster and bigger than the Industrial Revolution. If AI solves energy (fusion) and labor, we might enter a "post-scarcity" world. Hassabis warns that society, economics, and governments need to adapt quickly to ensure these benefits are shared by everyone, not just a few. And since this is the most important aspect, here is the clip about post labor economy:

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We’re using AI to work on root node problems – fundamental scientific challenges that unlock societal benefits. 🧪 From fusion and superconductors to entirely new materials, our CEO Demis Hassabis discusses what comes next after #AlphaFold – all on our podcast with Hannah Fry. ↓ Timecodes: 01:42 2025 progress 05:14 Jagged intelligence 07:32 Mathematical version of AlphaGo? 09:30 Science vs commercialization 12:42 Scaling 17:43 Genie and simulation 25:47 Evolution in simulation 28:26 AI bubble 31:56 Building ethical AI 34:31 AGI 44:44 Turing machines 49:06 How it feels to lead

We’re using AI to work on root node problems – fundamental scientific challenges that unlock societal benefits. 🧪 From fusion and superconductors to entirely new materials, our CEO Demis Hassabis discusses what comes next after #AlphaFold – all on our podcast with Hannah Fry. ↓ Timecodes: 01:42 2025 progress 05:14 Jagged intelligence 07:32 Mathematical version of AlphaGo? 09:30 Science vs commercialization 12:42 Scaling 17:43 Genie and simulation 25:47 Evolution in simulation 28:26 AI bubble 31:56 Building ethical AI 34:31 AGI 44:44 Turing machines 49:06 How it feels to lead

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In an era of geopolitical volatility, energy security is national security. The Turkish Path is our all-of-the-above blueprint to deliver reliable, affordable, and clean energy. By supercharging our renewable capacity, pioneering advanced nuclear infrastructure, unlocking entire domestic resources, and forging tier-one transatlantic partnerships, 🇹🇷Türkiye isn't just securing its own energy future, but anchoring the energy stability of the entire region. #TurkishPath in Energy.

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AI at scale is hitting a hard limit with energy. As AI infrastructure expands, power demand, not just compute architecture, is emerging as the gating constraint and pushing frontier builders toward vertically integrated deep tech bets spanning quantum discovery and fusion energy. Lenovo Data Center's Flynn Maloy and Jason Gibson, CEO and Co-founder of Quantum Formatics, discuss their collaboration to meet this challenge. They're betting on a dual-front strategy: leveraging quantum-driven simulation to accelerate material discovery while simultaneously pursuing fusion as the long-term energy unlock. Next-generation infrastructure requires breakthroughs not just in chips, but in the physical systems that power them.

AI at scale is hitting a hard limit with energy. As AI infrastructure expands, power demand, not just compute architecture, is emerging as the gating constraint and pushing frontier builders toward vertically integrated deep tech bets spanning quantum discovery and fusion energy. Lenovo Data Center's Flynn Maloy and Jason Gibson, CEO and Co-founder of Quantum Formatics, discuss their collaboration to meet this challenge. They're betting on a dual-front strategy: leveraging quantum-driven simulation to accelerate material discovery while simultaneously pursuing fusion as the long-term energy unlock. Next-generation infrastructure requires breakthroughs not just in chips, but in the physical systems that power them.

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The most skilled guy in the AI industry just said we're 1-2 breakthroughs away from AGI. And he explained exactly what's missing. Demis Hassabis runs Google DeepMind. He won the Nobel Prize in Chemistry last year. He's literally the reason why Google is considered the leader of the AI race. And he just dropped the most specific AGI timeline ever: "One or two AlphaGo-level technological breakthroughs." That's it. That's all standing between us and artificial general intelligence. But here's the thing... LLMs are NOT going to get us there. ChatGPT, Gemini, Claude - they're all hitting the same wall. They can't plan long-term. Can't create NEW ideas. Can't understand physics. Demis called them "jagged intelligences. Very good at certain things. Completely incapable of others." You've felt this yourself. You've felt this yourself. You ask ChatGPT a complex question and it sounds smart. But ask it to solve something that requires REASONING across multiple steps? It falls apart. So what ARE the 2 breakthroughs we need? Breakthrough #1: World Models AI that understands how physics actually works. How water flows. How cause and effect works. DeepMind already has early versions (Genie, Veo). The insight: If AI can GENERATE something realistic, it UNDERSTANDS it. This is the foundation for robotics and AI that interacts with reality. Breakthrough #2: Agentic Systems AI that can DO things. Not just answer questions. Plan multiple steps. Execute autonomously. Adjust when wrong. DeepMind proved this with AlphaGo in 2016 - planning 20+ moves ahead to beat the world champion. Now they're generalizing it to the real world. And here's the most interesting part: Demis says these two things are starting to CONVERGE. LLMs + World Models + Agentic Behavior = AGI And when I say converge, I mean Google is already building it. They're setting up the first fully automated scientific laboratory in the UK. No humans running experiments. AI designs the test. Robots execute it. AI analyzes results. AI adjusts and iterates. The lab will work on: → Room-temperature superconductors → Nuclear fusion materials → New battery chemistries → Climate tech breakthroughs Demis's logic is simple: "If AI can screen materials 100X faster, the energy revolution takes 10 years instead of 100." But here's the scary part: China is MONTHS behind. Not years. "They're very close to the frontier. Maybe only months behind." DeepSeek. Alibaba's Qwen models. They're catching up fast. And unlike what people thought, they're doing it WITHOUT access to the most advanced Nvidia chips. The window for the West to lead in AGI is shrinking. The economic impact? Demis: "10 times bigger than the Industrial Revolution. And maybe 10 times faster." Industrial Revolution took 100+ years and reshaped civilization. This will be 10X bigger in 1/10th the time. Mass job displacement. Economic restructuring. New industries overnight. But also: → Curing all disease → Solving climate change → Unlimited clean energy → "Radical abundance" Demis is betting DeepMind can get there first. Google spent $400 million on DeepMind in 2014. That stake is now worth 100s of billions. Because DeepMind is now the "engine room" of ALL of Google's AI. Every Gemini model. Every AI feature in Search, Gmail, Workspace. All built by DeepMind. Shipped across Google's dozens of billion-user products instantly. That distribution is their superpower. The final thing Demis said that stuck with me: "AGI is probably the most transformative moment in human history. And it's on the horizon." One or two breakthroughs and 5 years away. According to the most skilled guy in the industry.

The most skilled guy in the AI industry just said we're 1-2 breakthroughs away from AGI. And he explained exactly what's missing. Demis Hassabis runs Google DeepMind. He won the Nobel Prize in Chemistry last year. He's literally the reason why Google is considered the leader of the AI race. And he just dropped the most specific AGI timeline ever: "One or two AlphaGo-level technological breakthroughs." That's it. That's all standing between us and artificial general intelligence. But here's the thing... LLMs are NOT going to get us there. ChatGPT, Gemini, Claude - they're all hitting the same wall. They can't plan long-term. Can't create NEW ideas. Can't understand physics. Demis called them "jagged intelligences. Very good at certain things. Completely incapable of others." You've felt this yourself. You've felt this yourself. You ask ChatGPT a complex question and it sounds smart. But ask it to solve something that requires REASONING across multiple steps? It falls apart. So what ARE the 2 breakthroughs we need? Breakthrough #1: World Models AI that understands how physics actually works. How water flows. How cause and effect works. DeepMind already has early versions (Genie, Veo). The insight: If AI can GENERATE something realistic, it UNDERSTANDS it. This is the foundation for robotics and AI that interacts with reality. Breakthrough #2: Agentic Systems AI that can DO things. Not just answer questions. Plan multiple steps. Execute autonomously. Adjust when wrong. DeepMind proved this with AlphaGo in 2016 - planning 20+ moves ahead to beat the world champion. Now they're generalizing it to the real world. And here's the most interesting part: Demis says these two things are starting to CONVERGE. LLMs + World Models + Agentic Behavior = AGI And when I say converge, I mean Google is already building it. They're setting up the first fully automated scientific laboratory in the UK. No humans running experiments. AI designs the test. Robots execute it. AI analyzes results. AI adjusts and iterates. The lab will work on: → Room-temperature superconductors → Nuclear fusion materials → New battery chemistries → Climate tech breakthroughs Demis's logic is simple: "If AI can screen materials 100X faster, the energy revolution takes 10 years instead of 100." But here's the scary part: China is MONTHS behind. Not years. "They're very close to the frontier. Maybe only months behind." DeepSeek. Alibaba's Qwen models. They're catching up fast. And unlike what people thought, they're doing it WITHOUT access to the most advanced Nvidia chips. The window for the West to lead in AGI is shrinking. The economic impact? Demis: "10 times bigger than the Industrial Revolution. And maybe 10 times faster." Industrial Revolution took 100+ years and reshaped civilization. This will be 10X bigger in 1/10th the time. Mass job displacement. Economic restructuring. New industries overnight. But also: → Curing all disease → Solving climate change → Unlimited clean energy → "Radical abundance" Demis is betting DeepMind can get there first. Google spent $400 million on DeepMind in 2014. That stake is now worth 100s of billions. Because DeepMind is now the "engine room" of ALL of Google's AI. Every Gemini model. Every AI feature in Search, Gmail, Workspace. All built by DeepMind. Shipped across Google's dozens of billion-user products instantly. That distribution is their superpower. The final thing Demis said that stuck with me: "AGI is probably the most transformative moment in human history. And it's on the horizon." One or two breakthroughs and 5 years away. According to the most skilled guy in the industry.

Ricardo

217,113 просмотров • 6 месяцев назад

DeepMind’s Demis Hassabis: Elon is doing amazing things with SpaceX “I think there will be a solution to the energy problem. So free, pretty much free, renewable, clean energy one way or another, fusion or better solar. And then that will unlock us to really travel the stars. Because the main cost, Elon does amazing work with SpaceX and those things, but the main cost is still the rocket fuel, right? The energy cost. So if that's sort of zero somehow, because we can just make infinite rocket fuel out of seawater once we’ve cracked fusion.” Source: Muskonomy

DeepMind’s Demis Hassabis: Elon is doing amazing things with SpaceX “I think there will be a solution to the energy problem. So free, pretty much free, renewable, clean energy one way or another, fusion or better solar. And then that will unlock us to really travel the stars. Because the main cost, Elon does amazing work with SpaceX and those things, but the main cost is still the rocket fuel, right? The energy cost. So if that's sort of zero somehow, because we can just make infinite rocket fuel out of seawater once we’ve cracked fusion.” Source: Muskonomy

Mario Nawfal

215,453 просмотров • 3 месяцев назад

Demis Hassabis says AlphaFold was just the proof point for AI solving "root node" problems. "It feels like we've packed in 10 years in one year." "The big proof point was AlphaFold... that was the proof that it was possible to do these root node type of problems." "We're exploring all the other ones now. I think material science - I'd love to do a room-temperature superconductor... better batteries... better materials of all sorts." "We're also working on fusion." This is the AI shift founders keep underestimating: Not chatbots replacing search. Models becoming a discovery engine for the bottleneck problems under everything else - proteins, materials, batteries, fusion, robotics, medicine.

Demis Hassabis says AlphaFold was just the proof point for AI solving "root node" problems. "It feels like we've packed in 10 years in one year." "The big proof point was AlphaFold... that was the proof that it was possible to do these root node type of problems." "We're exploring all the other ones now. I think material science - I'd love to do a room-temperature superconductor... better batteries... better materials of all sorts." "We're also working on fusion." This is the AI shift founders keep underestimating: Not chatbots replacing search. Models becoming a discovery engine for the bottleneck problems under everything else - proteins, materials, batteries, fusion, robotics, medicine.

Karl Mehta

10,273 просмотров • 1 месяц назад

ELON: THE WORLD CAN BE POWERED ENTIRELY BY SOLAR AND BATTERIES “The energy that reaches the Earth from the Sun is staggeringly high. We have this enormous fusion generator in the sky that is lobbing out vast amounts of energy. If you take a nuclear plant, took its current output and compared that to putting solar panels on the area used by the nuclear power plant. The solar panels would typically generate more power than the nuclear power plant.” Source: Elon Musk

ELON: THE WORLD CAN BE POWERED ENTIRELY BY SOLAR AND BATTERIES “The energy that reaches the Earth from the Sun is staggeringly high. We have this enormous fusion generator in the sky that is lobbing out vast amounts of energy. If you take a nuclear plant, took its current output and compared that to putting solar panels on the area used by the nuclear power plant. The solar panels would typically generate more power than the nuclear power plant.” Source: Elon Musk

Mario Nawfal

46,577 просмотров • 1 год назад

"We sell energy, not nuclear reactors." - Isaiah Taylor - making nuclear reactors, founder of Valar Atomics "The best way to use a Falcon 9 at SpaceX is to own the entire operational cadence. You sell products like kgs to orbit and Internet connectivity." "Nuclear reactors are like this as well. You build reactors on large energy campuses, then sell energy to AI data centers which need hydrogen and synthetic fuels." "If we can make a synthetic fuel that's cheaper than diesel or gasoline, we can become the energy company of the world."

"We sell energy, not nuclear reactors." - Isaiah Taylor - making nuclear reactors, founder of Valar Atomics "The best way to use a Falcon 9 at SpaceX is to own the entire operational cadence. You sell products like kgs to orbit and Internet connectivity." "Nuclear reactors are like this as well. You build reactors on large energy campuses, then sell energy to AI data centers which need hydrogen and synthetic fuels." "If we can make a synthetic fuel that's cheaper than diesel or gasoline, we can become the energy company of the world."

TBPN

26,366 просмотров • 1 год назад