Pushmeet Kohli

When I was asked by the American Academy of Arts and Sciences to write an essay on my thoughts on how AI will accelerate Science, I felt honored but also felt that it would require a lot of thoughtfulness and diligence to distill my thoughts on paper. The essay has now been published and I cannot be more thankful to the @americanacad and @GoogleDeepMind teams for their feedback and encouragement during the process. Key reflections from my essay: 🔭 AI is our newest revolutionary lens: Just as the telescope and microscope expanded our physical perception, AI is extending our cognitive reach, allowing us to decipher the immense complexity of the data-universe. 🧬 The rise of "machine intuition": AI is not just a computational engine. By detecting hidden structures across disciplines—from protein folding to extremal combinatorics—it acts as an ultimate bridge, accelerating the interdisciplinary breakthroughs that modern science depends on. 🏗️ From puzzle-solvers to architects of questions: As we transition toward open-ended, agentic AI systems that actively generate novel hypotheses, the burden of reasoning is shifting. We are evolving from being the solvers of intricate puzzles into the architects of profound scientific questions. ✨ Expanding human potential: AI won't replace scientists; it expands what we can imagine and achieve. Just as the telescope didn't make astronomers obsolete, AI is giving us the stars. Read the full essay here: amacad.org/publication/da…

Our teams across @GoogleDeepMind and @googlecloud are working together to bring AlphaEvolve, our algorithm discovery and code optimization agent, to scientists and engineers solving the world's hardest technical problems. Looking forward to the new discoveries powered by AI! 👇

@JohnJumperSci , you have been a fantastic colleague. I am deeply grateful for all your invaluable contributions to the @GoogleDeepMind Science program. From the mission-focused execution on AlphaFold to the amazing Nobel ceremony- you leave us with a lot of memories. We wish you the best, my friend.

The next era of AI isn't just about writing code faster; it's about discovering entirely new ways to solve complex engineering bottlenecks. @GoogleDeepMind's evolutionary coding agent, AlphaEvolve, is now deployed on @googlecloud, acting as an autonomous research engineer for enterprise infrastructure. Instead of just generating boilerplate, it systematically explores and refines algorithmic search spaces. We are already seeing incredible empirical results in production: Logistics: @BASFAgro achieved an 80% accuracy improvement over their existing supply chain models. Core Systems: @jetbrains saw a 15-20% performance boost to their core IDE B-tree indexing stack. Read the full technical reports on how these algorithms are evolving here: 🔗 JetBrains: blog.jetbrains.com/ai/2026/05/how… 🔗 BASF: cloud.google.com/blog/products/…

We believe AI can be a dedicated research partner to help discover the next breakthrough. Enter Co-Scientist: our latest Gemini-based multi-agent system that can generate, debate and evolve novel hypotheses for complex scientific problems 🧵

Our team at DeepMind is growing. We've assembled a world class physics+material science team and are building an experimental lab. If you want to solve real problems at the intersection of AI + material science to unlock a technological revolution - this is the place. Apply 👇

See the formal proofs (in lean) discovered by the AlphaProof Nexus agent: github.com/google-deepmin…

AI agents are advancing research-level math. 🚀 I’m thrilled to share @GoogleDeepMind’s AlphaProof Nexus - an agentic framework for formal proof search powered by Gemini. When applied to a set of open formal math problems, our agent autonomously solved: ✅ 9 open Erdős problems (including two open for 56 years!) ✅ 44 Online Encyclopedia of Integer Sequences (OEIS) problems ✅ A 15-year-old open problem in algebraic geometry ✅ A 7-year-old open question in min-max optimization We are collaborating with mathematicians across disciplines - from combinatorics and graph theory to quantum optics. Ultimately, these results show the massive potential of even simple agentic loops powered by Gemini. Read the paper here: arxiv.org/abs/2605.22763…

@twominutepapers It's always great to talk to you, Károly. The love of research and science is strong in you - and long may it continue. @twominutepapers

It is such a joy - every time I talk to @pushmeet, I learn something new. 🙂

@GoogleDeepMind's SynthID has watermarked over 100 billion images and videos and 60,000 years of audio!SynthID has been used to verify content 50 million times globally! I am really happy to share that we @google are building on this momentum and expanding this verification capability to Search today and Chrome over the coming weeks. Read more at: blog.google/innovation-and…

Really happy to see @OpenAI adopt @GoogleDeepMind's SynthID for watermarking AI generated images. We need more such cross industry partnerships for enabling responsible use of AI systems.

The results of the research happening in my team @GoogleDeepMind have convinced me that the next era of scientific discovery will be aided by AI agents acting as force multipliers for human ingenuity. That’s why I’m proud to introduce Gemini for Science - a collection of experimental science tools designed to support researchers at every stage of the research process. The tools include: 1️⃣ Literature Insights, built with Google NotebookLM, searches millions of scientific papers to synthesize findings and generate artifacts including data tables, slides, reports, and more. 2️⃣ Hypothesis Generation, built with Co-Scientist, simulates the scientific method via a multi-agent "idea tournament" to generate, debate, and rigorously evaluate research hypotheses. 3️⃣Computational Discovery, built with AlphaEvolve and ERA, is an agentic engine that generates and scores thousands of code variations in parallel, allowing researchers to test modeling approaches in fields like epidemiology in a fraction of the usual time. Read more: blog.google/innovation-and… Register for access here: labs.google/science

Read more in our technical paper: arxiv.org/abs/2605.06651 See the Frontier Tier 4 problem evaluation at: epoch.ai/frontiermath/t…

The future of Math is mathematicians and AI agents working together. Very pleased to introduce @GoogleDeepMind's AI co-mathematician: a multi-agent system designed to actively collaborate with human experts on open-ended research mathematics. Mathematicians testing the agent across areas as diverse as group theory, Hamiltonian systems, and algebraic combinatorics have reported impressive results. In autonomous mode evaluation on the rigorous FrontierMath Tier 4 problems, AI co-mathematician scored an unprecedented 48% — a new high score among all AI systems evaluated.

Over the last few months, our team @GoogleDeepMind and @googlecloud has been putting our Gemini-powered algorithm discovery agent AlphaEvolve to work across a wide variety of important applications. The results are amazing! We're seeing major improvements in everything from chip design and genomics to logistics, electric grid optimization, and earth sciences. And this impact will only grow once it's used on more problems! 🚀 A perfect example of how AI agents will shape the world. Read more here: deepmind.google/blog/alphaevol…

One of @GoogleDeepMind's key aims is to unlock scientific progress on problems important for society. Generating clean energy is one of the biggest challenges of our time, and technologies like nuclear fusion could be the answer. While we continue to conduct our own research on this problem, our team has also been talking to experts across the field to understand the main AI opportunities and data obstacles, and to share recommendations to unlock faster progress. This kind of ‘AI Data Stocktake’ exercise can serve as a blueprint that policymakers, science funders, and industry can apply to many other scientific domains. Read more at: deepmind.google/public-policy/…