Learning

From recognising pictures of cats on the internet to defeating world champions in the game of Go, the power of Machine Learning is increasingly visible in our everyday lives. Many of the core ideas in modern machine learning can be traced to insights from studying learning in animals. However, the benefits from in both directions, with brain scientists using theories from optimal control, Bayesian decision-making, and predictive coding, to make sense of the changes that take place in the brain during learning. BCBT has featured many great talks about learning. Here we feature two talks, from Matthew Botvinick and Marc Toussaint, that applies principles from the study of predictive inference to understand learning in the brain, we also feature one of several talks that examine how the cerebellum contributes to learning skilled movements.