Abstract: What do we need to achieve artificial general intelligence? We will dive deep into the heart of the matter, which is machine reasoning. Following recent advances in mathematical foundations and homotopy type theory, we conclude that the crux is to formally separate intents from implementations. We can teach neural networks to understand these intents, and to use a divide-and-conquer method for compiling these intents into implementations. The goal of this talk is to outline future developments in AI, and to explore some of the consequences for the rest of us.
About the speaker: Dr. Shaowei Lin of the Singapore University of Technology and Design (SUTD). Dr. Lin is an Assistant Professor in the Engineering Systems and Design Pillar at SUTD. He received his Ph.D. in Mathematics in 2011 from the University of California, Berkeley. Before joining SUTD, he was the Deputy Head for Research in the Sense and Sense-abilities Programme in A*STAR, where he focused on deep learning for wireless sensor networks. His research interests are in distributed learning and reasoning for artificial intelligence.