How Physical Systems Can Learn by Themselves - Kirk Lecture

Explore a captivating lecture on self-learning physical systems delivered by Professor Andrea Liu from the University of Pennsylvania. Delve into the fascinating world of artificial neural networks and their biological inspirations. Discover the differences between top-down learning approaches requiring external computers and bottom-up learning methods observed in the brain. Gain insights into a novel approach for bottom-up learning that has been successfully implemented in physical systems, allowing them to learn autonomously. Understand the challenges of inverse design problems in neural networks and how AI techniques are being utilized to design physical systems that mimic biological functions. Engage with cutting-edge research at the intersection of statistical physics, neuroscience, and artificial intelligence in this thought-provoking Kirk Lecture presented at the Isaac Newton Institute for Mathematical Sciences.