1 h 30 min
What Does Machine Learning Have to Offer Mathematics? | Theoretically Speaking
Mathematics, Machine Learning, Artificial Intelligence and seminar by Jordan Ellenberg, University of Wisconsin–Madison
Hosted by Simons Institute for the Theory of Computing, UC Berkeley
Monday 17:30 Los Angeles (GMT-7)
Recording available
Berkeley, United States
Recording
Abstract
Jordan Ellenberg explores how machine learning might contribute to mathematical discovery. Drawing on collaborative work with DeepMind on a combinatorics problem, he considers the distinction between obeying formal rules and producing ideas that mathematicians judge important or ingenious, and discusses near-term changes to mathematical practice.
Topics
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