What Does Machine Learning Have to Offer Mathematics? - Theoretically Speaking

Explore the intersection of machine learning and mathematics in this thought-provoking lecture by Jordan Ellenberg, professor of mathematics at the University of Wisconsin–Madison. Delve into the potential of machines to prove theorems and generate mathematical ideas, focusing on Ellenberg's collaborative work with DeepMind researchers. Discover how novel machine learning techniques have advanced a problem in combinatorics and gain insights into the near-future impact of AI on mathematical practice. Learn about the unique challenges and opportunities presented by applying machine learning to mathematics, a field that combines well-defined rules with human assessments of ingenuity and importance. Gain valuable perspectives on the future of mathematical research and the role of artificial intelligence in pushing the boundaries of human knowledge.

What Does Machine Learning Have to Offer Mathematics? | Theoretically Speaking