Memory, Modularity, and the Theory of Deep Learnability

A Google TechTalk, 2019/04/04, presented by Rina Panigrahy. ABSTRACT: Why does deep learning work well for some applications and not for others? Do we need major architectural changes in deep learning to solve complex problems like natural language understanding and logic? Does memory and modular organization play an important role, and if so, how do we store complex concepts in memory? We will try to get a conceptual understanding of these questions by studying learning problems arising from synthetic mat