Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Demis Hassabis explains that tasks like coding and math are easier to automate because they offer clear, verifiable outputs. However, scientific discovery like creating new hypotheses or theories is much harder for AI. It’s not just about solving known problems, but inventing new questions, which requires a higher level...

WesRoth's profile picture

Wes Roth

28,471 subscribers

15,090 görüntüleme • 5 ay önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Demis Hassabis on the final frontier for AI in science 🧬 : it’s not just about solving the math, it’s about having the creativity to ask the question in the first place. While coding and math are verifiable and easier to automate, natural science requires a "missing ingredient" that we haven't fully cracked yet. "Coming up with the question in the first place or coming up with the theory or the hypothesis. I think that's much, much harder and I think that's the highest level of scientific creativity.”
1:50

Demis Hassabis on the final frontier for AI in science 🧬 : it’s not just about solving the math, it’s about having the creativity to ask the question in the first place. While coding and math are verifiable and easier to automate, natural science requires a "missing ingredient" that we haven't fully cracked yet. "Coming up with the question in the first place or coming up with the theory or the hypothesis. I think that's much, much harder and I think that's the highest level of scientific creativity.”

Chris

12,885 görüntüleme • 5 ay önce

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.
2:22

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 görüntüleme • 5 ay önce

“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.
0:53

“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.

Jon Hernandez

25,478 görüntüleme • 1 ay önce

Demis Hassabis says we shouldn't treat AGI as a marketing term But as a system that exhibits all human cognitive capabilities, including physical intelligence It must go beyond solving math problems to true invention, creating new theories like Einstein or new art genres like Picasso "today's systems are nowhere near that"
1:51

Demis Hassabis says we shouldn't treat AGI as a marketing term But as a system that exhibits all human cognitive capabilities, including physical intelligence It must go beyond solving math problems to true invention, creating new theories like Einstein or new art genres like Picasso "today's systems are nowhere near that"

Haider.

18,918 görüntüleme • 5 ay önce

📁 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.
2:17

📁 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 görüntüleme • 10 ay önce

📁 Demis Hassabis says that one of the main reasons we are not yet at AGI is the lack of consistency. He explains that current systems can solve International Math Olympiad level problems but still fail at basic logic tasks or even chess. They are uneven intelligences, exceptional in some areas and surprisingly weak in others, which falls short of true AGI.
1:01

📁 Demis Hassabis says that one of the main reasons we are not yet at AGI is the lack of consistency. He explains that current systems can solve International Math Olympiad level problems but still fail at basic logic tasks or even chess. They are uneven intelligences, exceptional in some areas and surprisingly weak in others, which falls short of true AGI.

Jon Hernandez

10,541 görüntüleme • 6 ay önce

Watch Demis Hassabis and Matt Clifford discuss how AI can accelerate scientific discovery and how multimodality puts us on the path to human-level AI. Demis and Matt—thank you for your insights.
2:39

Watch Demis Hassabis and Matt Clifford discuss how AI can accelerate scientific discovery and how multimodality puts us on the path to human-level AI. Demis and Matt—thank you for your insights.

David Singleton

59,247 görüntüleme • 2 yıl önce

📁 Demis Hassabis, CEO of DeepMind, says AI is still missing critical capabilities. He explains that current systems cannot plan far ahead or reason like top human scientists, because they lack a deep model of the world. They can process text, images, and video, but they still don’t understand physics, causality, or how actions affect outcomes over time.
1:00

📁 Demis Hassabis, CEO of DeepMind, says AI is still missing critical capabilities. He explains that current systems cannot plan far ahead or reason like top human scientists, because they lack a deep model of the world. They can process text, images, and video, but they still don’t understand physics, causality, or how actions affect outcomes over time.

Jon Hernandez

63,723 görüntüleme • 5 ay önce

Yann Lecun says his estimate for the creation of human-level AI is not that different from Sam Altman or Demis Hassabis - it is possible within 5-10 years
1:21

Yann Lecun says his estimate for the creation of human-level AI is not that different from Sam Altman or Demis Hassabis - it is possible within 5-10 years

Tsarathustra

357,202 görüntüleme • 1 yıl önce

3/ From Analytical to Creative AI Today's AI can't imagine or create new ideas. "They can't ask novel questions or form new hypotheses." In 5-10 years, this changes. When AI starts creating original scientific theories, entire industries transform overnight.
0:47

3/ From Analytical to Creative AI Today's AI can't imagine or create new ideas. "They can't ask novel questions or form new hypotheses." In 5-10 years, this changes. When AI starts creating original scientific theories, entire industries transform overnight.

Karl Mehta

92,633 görüntüleme • 1 yıl önce

Demis Hassabis says the next frontier is AI self-improvement — and coding is where it starts, because the outputs are verifiable and synthetic data is limitless That's a compounding flywheel, and every major lab is betting on it "but raw capability without reliability is a liability"
1:20

Demis Hassabis says the next frontier is AI self-improvement — and coding is where it starts, because the outputs are verifiable and synthetic data is limitless That's a compounding flywheel, and every major lab is betting on it "but raw capability without reliability is a liability"

Haider.

15,427 görüntüleme • 1 ay önce

I’m fully with Demis Hassabis on this. STEM still matters deeply, not because humans will outcode AI, but because we need to understand, steer, and define problems at a high level. At the same time, AI is blowing the doors open for creativity. When technical barriers fall, taste, judgment, and vision become the real edge. The future belongs to people who know what to build and why, not just how. Do you think schools are preparing kids for that reality or are they still training them for a world that’s already gone?
0:37

I’m fully with Demis Hassabis on this. STEM still matters deeply, not because humans will outcode AI, but because we need to understand, steer, and define problems at a high level. At the same time, AI is blowing the doors open for creativity. When technical barriers fall, taste, judgment, and vision become the real edge. The future belongs to people who know what to build and why, not just how. Do you think schools are preparing kids for that reality or are they still training them for a world that’s already gone?

VraserX e/acc

58,341 görüntüleme • 4 ay önce

Demis Hassabis, CEO of Google DeepMind, drops a quiet bombshell: The big question isn’t whether AI can solve problems. It’s whether AI can invent new science. Right now, it can’t. Not because of compute. Not because of data. But because it lacks something fundamental: A world model. Today’s LLMs can generate brilliant text, images, even code. But they don’t truly understand causality. They don’t know why A leads to B. They just predict patterns. Hassabis argues that real scientific discovery requires more: – Long-term planning – Stronger reasoning – And an internal model of how the world works Physics. Biology. Cause and effect. Only then can an AI run its own thought experiments. Only then do we get a true digital scientist.
1:47

Demis Hassabis, CEO of Google DeepMind, drops a quiet bombshell: The big question isn’t whether AI can solve problems. It’s whether AI can invent new science. Right now, it can’t. Not because of compute. Not because of data. But because it lacks something fundamental: A world model. Today’s LLMs can generate brilliant text, images, even code. But they don’t truly understand causality. They don’t know why A leads to B. They just predict patterns. Hassabis argues that real scientific discovery requires more: – Long-term planning – Stronger reasoning – And an internal model of how the world works Physics. Biology. Cause and effect. Only then can an AI run its own thought experiments. Only then do we get a true digital scientist.

VraserX e/acc

167,167 görüntüleme • 5 ay önce

AI for Scientific Advancement Diana AI is transforming how physical things are made. Many scientific tools haven’t changed in decades, but test-time compute is now enabling new startups to solve complex problems in fields like chemistry, biology, and materials science.
0:36

AI for Scientific Advancement Diana AI is transforming how physical things are made. Many scientific tools haven’t changed in decades, but test-time compute is now enabling new startups to solve complex problems in fields like chemistry, biology, and materials science.

Y Combinator

17,689 görüntüleme • 1 yıl önce

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.
1:07

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 görüntüleme • 5 ay önce

Columbia CS Prof explains why LLMs can’t generate new scientific ideas. Bcz LLMs learn a structured “map”, Bayesian manifold, of known data and work well within it, but fail outside it. But true discovery means creating new maps, which LLMs cannot do.
50:47

Columbia CS Prof explains why LLMs can’t generate new scientific ideas. Bcz LLMs learn a structured “map”, Bayesian manifold, of known data and work well within it, but fail outside it. But true discovery means creating new maps, which LLMs cannot do.

Rohan Paul

759,676 görüntüleme • 8 ay önce

Sam Altman says AI reasoning is still at the GPT-2 stage but the improvement curve is steep and the new o1 model represents a new paradigm of AI development which will enable rapid progress in capabilities
2:07

Sam Altman says AI reasoning is still at the GPT-2 stage but the improvement curve is steep and the new o1 model represents a new paradigm of AI development which will enable rapid progress in capabilities

Tsarathustra

419,003 görüntüleme • 1 yıl önce

Stephen C. Meyer says Darwin’s theory of evolution has, for many, become more like a religion than a scientific theory. “Darwinian evolution functions as a kind of secular religion.” “And you can see why, because it's answering one of the most fundamental questions that any worldview or religion has to answer.” “Which is what is the thing or the entity or the process from which everything else came?” “And the neo-Darwinian explanation of the origin of new forms of life is part of the answer to that really fundamental question, which is not only a scientific question but a philosophical worldview question.” “Because it functions like a secular religion, sometimes there's resistance to a more dispassionate scientific evaluation of its merits.” Stephen C. Meyer
0:54

Stephen C. Meyer says Darwin’s theory of evolution has, for many, become more like a religion than a scientific theory. “Darwinian evolution functions as a kind of secular religion.” “And you can see why, because it's answering one of the most fundamental questions that any worldview or religion has to answer.” “Which is what is the thing or the entity or the process from which everything else came?” “And the neo-Darwinian explanation of the origin of new forms of life is part of the answer to that really fundamental question, which is not only a scientific question but a philosophical worldview question.” “Because it functions like a secular religion, sometimes there's resistance to a more dispassionate scientific evaluation of its merits.” Stephen C. Meyer

Jan Jekielek

199,433 görüntüleme • 2 ay önce