Overflow: Pursuing the Nature of Intelligence

In this talk, we will try to clarify different levels and mechanisms of intelligence from historical, scientific, mathematical, and computational perspective. From the evolution of intelligence in nature, from phylogenetic, to ontogenetic, to societal, and to artificial intelligence, we will try to shed light on how to understand the true nature of the seemingly dramatic advancements in the technologies of machine intelligence in the past decade. We achieve this goal by developing a principled mathematical framework to explain the practice of deep learning from the perspective of compressive data encoding and decoding. This framework not only reveals true nature hence limitations of the current practice and but also provides principled guidelines to develop more complete and more efficient learning architectures and systems. Eventually, we will clarify the difference and relationship between Knowledge and Intelligence, which may guide us to pursue the goal of developing systems with true intelligence.