"What I cannot create, I do not understand". That credo was deeply important to Richard Feynman, and I think it should be important for anyone trying to understand complex systems. Here at the Centre for Theoretical Neuroscience at the University of Waterloo, we've been trying to apply this idea to understanding the human brain. We have been making large-scale simulations of the human brain in order to test theories about how the brain works. The result of this is Spaun, the first brain model that can actually perform very basic tasks, such as recognizing numbers, remembering a list, counting, and completing patterns. In this talk, we will talk about Spaun, the technical and theoretical challenges in its creation, what we have learned from it about human cognition, and where we are going from here.
Terry Stewart started as an Engineer (Systems Design at Waterloo), where he built robots and dabbled in cognitive science. Then he did a Masters of Philosophy in Computer Science and AI (Sussex University), which turned out to involve doing experimental psychology on robots.
His PhD in Cognitive Science (Carleton University) examined how computational models are used and how they ought to be used to understand the mind. He is currently a postdoctoral research associate in the Centre for Theoretical Neuroscience (here at Waterloo).
Friday, November 15, 2013
Environment 3, room 1408