Explore the second lecture in a series on how materials can learn by themselves, delivered by Andrea J Liu from the University of Pennsylvania. Delve into the fascinating world of artificial neural networks and their application in solving inverse design problems in soft matter. Discover how approaches developed by computer scientists are being harnessed to design mechanical and flow networks that perform functions inspired by biology. Learn about the pioneering work on bottom-up learning, a new approach that allows physical systems to learn autonomously, overcoming the constraints of traditional top-down learning methods. Gain insights from Liu, a renowned theoretical soft and living matter physicist, as she shares her expertise in this cutting-edge field of materials science and physics.