How to Explain Deep Learning using Chaos and Complexity – Intuition Machine

I want to talk to you today about the concerns of Non-Equilibrium Information Dynamics and how an understanding of its features lead us to a better intuition about Deep Learning systems or learning systems in general. Allow me to recap my observation from a previous post on "Deep Learning in Non-Equilibrium Dynamics". In our study of Deep Learning, practitioners derive their intuition from the mathematics of physical systems. However, since these are not a physical system that we study but rather information systems, we apply information-theoretic principles. Now, information theory has its origins also in mathematics that describe physics (i.e.