DeepMind’s AI for Mathematics Breakthrough Explained

#DeepMind #AI #math #machine #learning #knot #theory DeepMind recently published a paper in Nature proposing a new paradigm for how machine learning can be used to help mathematicians pose new conjectures and ultimately prove new theorems. This methodology was used to establish breakthrough results in mathematics by discovering new connections in knot theory (a relationship between algebraic and geometric knot invariants) and making significant progress on a 40 year old conjecture in representation theory. In this video, I explain in depth the knot theory result by providing a soft introduction to the knot theory, a rapid crash course in supervised machine learning, and then diving into the paper. The paper: “Advancing mathematics by guiding human intuition with AI“ Acknowledgments: Alex Davies, Andras Juhasz, Marc Lackenby generously offered their consultation for the production of this video. (Of course, any deficiencies of the video are due to me). Dis