Hierarchical AI - from neurons to psychology

Abstract

The undeniable successes of deep learning (and more generally statistical learning) in bringing pattern matching to the market is still just the tip of the iceberg of AI. In this talk we will look at a very high level overview of AI as a whole and see how it can be interpreted at very different levels of abstraction. Each level of abstraction boasts its own vocabulary and is suited to understanding different aspects of the general problem of artificial intelligence. We will walk through four “levels of abstraction of AI” ranging from physical implementation all the way to semantic processing, and will investigate how memory technologies can play a vital role in their successful implementation. The aim is to show how innovation in the domain of memory tech can unlock the potential of AI to attack problems much more general than simple pattern matching and thus pave the way to the next wave of AI on the market.