DeepMind's Pushmeet Kohli on AI's Scientific Revolution
Pushmeet Kohli leads AI for Science at DeepMind, where his team has created AlphaEvolve, an AI system that discovers entirely new algorithms and proves mathematical results that have eluded researchers for decades. From improving 50-year-old matrix multiplication algorithms to generating interpretable code for complex problems like data center scheduling, AlphaEvolve represents a new paradigm where LLMs coupled with evolutionary search can outperform human experts. Pushmeet explains the technical architecture behind these breakthroughs and shares insights from collaborations with mathematicians like Terence Tao, while discussing how AI is accelerating scientific discovery across domains from chip design to materials science.
Hosted by Sonya Huang and Pat Grady, Sequoia Capital
Meet AlphaEvolve: The Autonomous Agent That Discovers Algorithms Better Than Humans With Google DeepMind’s Pushmeet Kohli and Matej Balog
Much of the scientific process involves searching. But rather than continue to rely on the luck of discovery, Google DeepMind has engineered a more efficient AI agent that mines complex spaces to facilitate scientific breakthroughs. Sarah Guo speaks with Pushmeet Kohli, VP of Science and Strategic Initiatives, and research scientist Matej Balog at Google DeepMind about AlphaEvolve, an autonomous coding agent they developed that finds new algorithms through evolutionary search. Pushmeet and Matej talk about how AlphaEvolve tackles the problem of matrix multiplication efficiency, scaling and iteration in problem solving, and whether or not this means we are at self-improving AI. Together, they also explore the implications AlphaEvolve has to other sciences beyond mathematics and computer science.
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Chapters:
00:00 Pushmeet Kohli and Matej Balog Introduction
0:48 Origin of AlphaEvolve
02:31 AlphaEvolve’s Progression from AlphaGo and AlphaTensor
08:02 The Open Problem of Matrix Multiplication Efficiency
11:18 How AlphaEvolve Evolves Code
14:43 Scaling and Predicting Iterations
16:52 Implications for Coding Agents
19:42 Overcoming Limits of Automated Evaluators
25:21 Are We At Self-Improving AI?
28:10 Effects on Scientific Discovery and Mathematics
31:50 Role of Human Scientists with AlphaEvolve
38:30 Making AlphaEvolve Broadly Accessible
40:18 Applying AlphaEvolve Within Google
41:39 Conclusion
The Zoom Election + Google DeepMind's Math Olympiad + HatGPT! Olympics Edition
This week, with hundreds of thousands of people joining online political rallies for Kamala Harris, we discuss whether 2024 is suddenly becoming the Zoom election, and what that means for both parties’ political organizing. Then, Pushmeet Kohli, a computer scientist at Google DeepMind, joins us for a conversation about how his team’s new A.I. models just hit a silver medal score on the International Mathematical Olympiad exam. And finally, it’s time for a new round of HatGPT! This time, it’s a special Olympics tech edition.
Guest:
Pushmeet Kohli, vice president of research at Google DeepMind
Additional Reading:
Liberal “White Dudes” Rally for Harris: “It’s Like a Rainbow of Beige”
Move Over, Mathematicians, Here Comes AlphaProof
Now Narrating the Olympics: A.I.-Al Michaels
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Can AI Advance Science? DeepMind's VP of Science Weighs In
In recent years, the AI landscape has seen huge advancements, from the release of Dall-E 2 in April 2022 to the emergence of AI music and video models in early 2024.
While creative tools often steal the spotlight, AlphaFold 2 marked a groundbreaking AI breakthrough in biology in 2021. Since its release, this pioneering tool for predicting protein structures has been utilized by over 1.7 million scientists worldwide, influencing fields ranging from genomics to computational chemistry.
In this episode, DeepMind's VP of Research for Science, Pushmeet Kohli, and a16z General Partner Vijay Pande discuss the transformative potential of AI in scientific exploration. Can AI lead to fundamentally new discoveries in science? Let's find out.
Resources:
Find Pushmeet on Twitter: https://twitter.com/pushmeet
Find Vijay on Twitter: https://twitter.com/vijaypande
Learn more about Google DeepMind: https://deepmind.google
Read DeepMind’s AlphaFold whitepaper: https://deepmind.google/discover/blog/a-glimpse-of-the-next-generation-of-alphafold
Read DeepMind’s AlphaGeometry: https://deepmind.google/discover/blog/alphageometry-an-olympiad-level-ai-system-for-geometry
Read DeepMind’s research on new materials: https://deepmind.google/discover/blog/millions-of-new-materials-discovered-with-deep-learning/
Read DeepMind’s paper on FunSearch, focused on new discoveries in mathematics: https://deepmind.google/discover/blog/funsearch-making-new-discoveries-in-mathematical-sciences-using-large-language-models
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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DeepMind for Science, sponsored by Clear.ML
Pushmeet Kohli, the head of DeepMind's AI for Science and one of the brains behind AlphaFold, the machine learning system that is helping solve the protein folding problem. The episode is sponsored by Clear.ML, an open-source MLOps solution.