AI for Math

This is a participating seminar organized by Ivan Losev and Ro Wang. Its primary audience is Yale Math graduate students and its goal is to explain how one could and should use AI for Math research and education. Participants are strongly encouraged to make presentations on various aspects of using AI for Math!

Some online resources: Keep in mind that views expressed in these pieces are not necessarily shared by the organizers.

  • Pavel Etingof's note on use of AI for Math research.
  • Lisa Carbone's note on advancing Math research using AI.
  • Leiden declaration on AI and Math.
  • The letter on severe misalignment of AI in Math.
  • Discussions on AI and Math organized by Martin Bauer.
  • A summary of Terry Tao's posts and interview on AI and Math.
  • Alex Kontorovich's ICM plenary lecture.
  • The webpage of Summit on Math Ph.D. education in the age of AI. It has a report.
  • MIT's Math department webpage on the matter.
  • Recommendations on doctoral advising from AHM.

    Schedule:

  • Oct 2 (3.40-4.40 on zoom): organizational meeting followed by a presentation by Ro.
  • Oct 8, 4.15-5.15: A talk by Daniell Litt on AI for mathematical understanding. Consult with the announcement for the location.
  • Oct 9, 3.40-4-40 on zoom: Ro will make a presentation and demonstrate some of his own work with AI.
  • Oct 16, 3.40-4.40 on zoom: Charlie Smart will talk about automated proof verification.
  • Oct 23: break, no seminar.
  • Oct 30: Gal Yehuda speaks on: "Magical LLMs and how to train them". In his talk Gal plans to sketch the way LLMs work: their architecture, training process, and the math underlying them.