1 h 16 min
AI for Formal Math, and Physics, and why they're different
Artificial Intelligence, Machine Learning, Mathematics and seminar by Alexander Meiburg, Perimeter Institute for Theoretical Physics
Wednesday 11:00 Toronto (GMT-4)
Recording available
Waterloo, Canada
Recording
Abstract
Alexander Meiburg examines how language models and interactive theorem provers are changing AI-assisted mathematics. Models can propose creative natural-language arguments but also make subtle errors; formal proof systems provide grounding. The talk discusses model development, strengths and weaknesses, and the differences involved in extending formal assistance to physics, where establishing suitable definitions can be a larger obstacle than proving statements.
Topics
language modelsinteractive theorem proversAI-assisted mathematicsnatural-language argumentsformal proof systemsModel Developmentformal assistancePhysics
Show 1 more topic
definitions
Related seminars
Mathematics in the Age of AI: Discovery, Reasoning, Verification, and Unease
Oct 20, 2026Ken Ono, University of Virginia and Axiom MathMachine-Checked Proofs and the Rise of Formal Methods in Mathematics | Theoretically Speaking
Video · 1 h 25 min · Captions · Oct 6, 2023Leonardo de Moura, AWSAI is a tool: A working mathematician's experience and perspective
Nov 16, 2026Martin Raum, Chalmers University of Technology
More from Perimeter Institute for Theoretical Physics
All talksTropical quantum field theory
Video · 1 h 8 min · Oct 14, 2026Michael BorinskyComputational Bounds for f -Routing
Video · 1 h · Oct 14, 2026Oren RenardBig Boxes, Not Black Boxes: What we can compute about LLMs, and what it may say about AGI
Oct 7, 2026Zohar RingelSelf-consistent entanglement certification and its complexity.
Video · 1 h 10 min · Oct 7, 2026Yujie Zhang
Upcoming in Artificial Intelligence
All seminarsHow to address the use of AI in physical science and education?
Nov 3, 2026Armin TavakoliAI That Thinks Differently: Seeing, Understanding, and Trusting Visual Data in the Age of Foundation Models
Oct 28, 2026Manoranjan PaulGenerative Questions About Generative AI in Math Learning
Oct 20, 2026Dan Meyer