AI and number theory

May 27 to May 30, 2026

at the

American Institute of Mathematics, Pasadena, California

organized by

Tudor Achim, Brian Conrey, David Farmer, Alex Meiburg, and Michael Rubinstein

Original Announcement

This workshop is motivated by the very general questions: What problems in research mathematics are amenable to attack by AI, and how can general AI be improved to be more successful, and more widely applicable, to research mathematics?

The workshop will focus specifically on problems in number theory. Two categories within that area will receive particular attention:

Improving bounds in theorems, both at the level of main terms and lower order terms
algorithms: improving existing algorithms and implementing new ones

Each problem in these areas could potentially serve as a benchmark for testing the capabilities of general AI. An outcome of the workshop will be a curated list of interesting problems, several of which have been converted into official benchmarks with an indication of the current limits of AI. The list will serve as a permanent and growing resource for research mathematicians and AI developers.

Material from the workshop

A list of participants.

The workshop schedule.

Workshop videos