Mathematics is the foundational language of the universe, providing the tools to describe everything from the laws of physics to the intricacies of biology and the logic of computer science. For centuries, its frontiers have been expanded by human ingenuity alone. At Google DeepMind, we believe AI can serve as a powerful tool to collaborate with mathematicians, augmenting creativity and accelerating discovery.

Today, we’re introducing the AI for Math Initiative, supported by Google DeepMind and Google.org. It brings together five of the world's most prestigious research institutions to pioneer the use of AI in mathematical research.

The inaugural partner institutions are:

• Imperial College London
• Institute for Advanced Study
• Institut des Hautes Études Scientifiques (IHES)
• Simons Institute for the Theory of Computing (UC Berkeley)
• Tata Institute of Fundamental Research (TIFR)

The initiative’s partners will work towards the shared goals of identifying the next generation of mathematical problems ripe for AI-driven insights, building the infrastructure and tools to power these advances and, ultimately, accelerating the pace of discovery.

Google’s support includes funding from Google.org and access to Google DeepMind’s state-of-the-art technologies, such as an enhanced reasoning mode called Gemini Deep Think, our agent for algorithm discovery, AlphaEvolve, and our formal proof completion system, AlphaProof. The initiative will create a powerful feedback loop between fundamental research and applied AI, opening the door to deeper partnerships.

A pivotal moment for AI and mathematics

The AI for Math Initiative comes at a time of remarkable progress in AI’s reasoning capabilities; our own work has seen rapid advancement in recent months.

In 2024, our AlphaGeometry and AlphaProof systems achieved a silver-medal standard at the International Mathematical Olympiad (IMO). More recently, our latest Gemini model, equipped with Deep Think, achieved a gold-medal level performance at this year’s IMO, perfectly solving five of the six problems and scoring 35 points.

And we’ve seen further progress with another of our methods, AlphaEvolve, which was applied to over 50 open problems in mathematical analysis, geometry, combinatorics and number theory and improved the previously best known solutions in 20% of them. In mathematics and algorithm discovery, it has invented a new, more efficient method for matrix multiplication — a core calculation in computing. For the specific problem of multiplying 4x4 matrices, AlphaEvolve discovered an algorithm using just 48 scalar multiplications, breaking the 50-year-old record set by Strassen’s algorithm in 1969. In computer science, it helped researchers discover new mathematical structures that show certain complex problems are even harder for computers to solve than we previously knew. This gives us a clearer and more precise understanding of computational limits, which will help guide future research.

This rapid progress is a testament to the fast-evolving capabilities of AI models. We hope this new initiative can explore how AI can accelerate discovery in mathematical research, and tackle harder problems.

We are only at the beginning of understanding everything AI can do, and how it can help us think about the deepest questions in science. By combining the profound intuition of world-leading mathematicians with the novel capabilities of AI, we believe new pathways of research can be opened, advancing human knowledge and moving toward new breakthroughs across the scientific disciplines.