We are currently in the midst of a revolution in artificial intelligence. Biologically-inspired deep neural networks have produced a dizzying array of engineering feats in just the past few years, meeting or exceeding human performance on tasks like object recognition, machine translation, video gameplay, and even disease diagnosis. Given this success, it is natural to ask whether artificial neural networks might have something to tell us about how our brains work. In this seminar, speakers working at the intersection of neuroscience, philosophy, and artificial intelligence will tackle this question, drawing on recent research that attempts to use artificial neural networks as models of the brain.
Daniel Yamins, Assistant Professor of Psychology and Computer Science, Stanford University
Rosa Cao, Assistant Professor of Philosophy, Stanford University
Aude Oliva, Director, MIT-IBM Watson AI Lab, Co-Director, MIT Quest for Intelligence, MIT