Insights from Quantum Field Theory and AdS/CFT for Machine Learning

Explore a 91-minute seminar lecture where Professor Johanna Erdmenger from Julius-Maximilians-Universität Würzburg delves into the fascinating intersections between quantum field theory, AdS/CFT correspondence, and machine learning. Discover how recent developments in information theory and quantum gravity have led to new understandings of black holes through the lens of the AdS/CFT correspondence. Learn about the application of fundamental physics concepts like renormalization group and relative entropy in quantifying neural network learning capabilities, and understand how hyperbolic geometry contributes to enhanced neural network properties. Part of the "Black holes: bridges between number theory and holographic quantum information" event series, gain insights into the emerging connections between quantum physics and modern machine learning approaches.