arXiv:2608.23218v1 Announce Type: new Abstract: Advances in neural theorem provers have been impressive, but the successes obscure a broader vision of what AI can do for mathematics and how mathemati...
Advances in neural theorem provers have been impressive, but the successes obscure a broader vision of what AI can do for mathematics and how mathematicians can engage with AI. This essay advances a m...
The initiative brings together some of the world's most prestigious research institutions to pioneer the use of AI in mathematical research.
The article "Math for AI safety: an invitation for mathematicians" calls for new mathematical tools to ensure AI remains understandable, controllable, and cooperative. It outlines specific mathematical fields—logic, game theory, probability, algebra, representation theory, analysis, and geometry—each paired with an open problem tailored for mathematicians without AI safety background. The piece invites researchers to contribute to designing AI that is legible, steerable, and aligned with human values.
We’ve trained a system that solves grade school math problems with nearly twice the accuracy of a fine-tuned GPT-3 model. It solves about 90% as many problems as real kids: a small sample of 9-12 year olds scored 60% on a test from our dataset, while our system scored 55% on those same problems.
The International Mathematical Olympiad (“IMO”) is the world’s most prestigious competition for young mathematicians, and has been held annually since 1959. Each country taking part is represented by six elite, pre-university mathematicians who compete to solve six exceptionally difficult problems in algebra, combinatorics, geometry, and number theory.
Between April 1 and May 15, 2026, a group of 49 mathematicians compiled a dataset of research-level mathematics questions with known answers. Most of the work was done during the 3-day workshop *Benchmarks in Leipzig* with 35 participants at the Max Planck Institute for Mathematics in the Sciences in Leipzig, Germany.
Two open problems, exact-arithmetic checking and a proof assistant, over a single weekend. The post Mathematical Experiments Are Becoming Abundant Through Human-Machine Teaming appeared first on Towards Data Science .
AI agents are increasingly used in mathematics research, but it is often unclear how to use them effectively. Towards this, we present an extensive case study of how AI was used to improve bounds on the Grothendieck constant $K_G$, which captures the hardness between combinatorial problems and their continuous relaxations.
