Can we teach AI to learn from it’s own experiences? That’s the premise behind reinforcement learning. Dr. Rich Sutton in a University of Alberta Professor in computer science and one of the leading figures in AI research today. We talk about the early days of his career, why he chose to make the University of Alberta his academic home, the benefits of not chasing fads and the importance of an interdisciplinary AI research community. We also explore reinforcement learning and how it shifts not only the ways in which we develop AI, but also how we might think about our relationship with AI.  “The data a reinforcement learning agent uses the data it generates itself…you’re an (AI) agent, you’ve done some things, you’ve seen some things, it’s your data…that’s what you learn from (in reinforcement learning).” – Rich Sutton Dr. Rich Sutton is a distinguished research scientist at DeepMind, a professor in the department of computing science at the University of Alberta and a Fellow of the Alberta Machine Intelligence Institute (Amii). He is one of the pioneers of reinforcement learning and co-authored the textbook Reinforcement Learning: An Introduction. His research interests center on the learning problems facing a decision-maker interacting with its environment, which he sees as central to artificial intelligence.