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/daeda…

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/2026/0… 🔗 BASF: cloud.google.com/blog/produc…

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 👇

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-a… Register for access here: labs.google/science

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/alphaev…

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-polic…

I am happy to introduce AI co-clinician, @GoogleDeepMind's research initiative to explore how AI could better amplify doctor's expertise and help deliver higher quality care to patients. We’re excited about our early results, and are taking a phased approach to our research explorations with academic and research collaborators. Read more in our blog: deepmind.google/blog/ai-co-c…

Incredibly rewarding to see foundational AI research translate into tools that millions of people rely on. @GoogleDeepMind's AlphaEarth model is now powering high-resolution precise pollen maps for @googlemaps and Pixel Weather in the US - just in time for allergy season! 🌳🤧 Here’s an example showing pollen-producing Maple trees in New Jersey

Just back from an inspiring trip to Singapore 🇸🇬 where I met Theodore Kwan, an 8-year-old! chemistry whiz who is already using AlphaFold to explore and learn more about conditions like cystic fibrosis with his mum. It’s great to see @GoogleDeepMind's AlphaFold model inspiring the next generation of scientists :) Read more about him at: straitstimes.com/singapore/p…