CTN: Mazviita Chirimuuta
January 10 @ 11:30 am - 1:00 pm
Title: Neuromorphic Computing and the Significance of Medium Dependence
Abstract:
The increasingly prohibitive cost of energy demanded by large artificial neural networks (ANNs) is giving new impetus to research and development on neuromorphic computing. Importantly, there is an open question over how brain-like the hardware will have to be in order for an artificial intelligence to match the brain in its combination of robustness, adaptability, and energy efficiency. If biological cognition is heavily dependent on the specific properties of the material that instantiates it (i.e. living cells), then neuromorphic computing will have to merge with synthetic biology in order to achieve its ultimate goal of brain-like performance. If it is not, neuromorphic computing holds out the promise of some gains in efficiency but there is no pressure for hardware to become increasingly neuro-mimetic in order to match the functionality of the nervous system. In this talk I introduce the concept of practical medium dependence/independence in order to explore the likelihood of these two scenarios. I present the argument that practically medium independent approaches to information processing, such as digital computing, are inherently less efficient than ones dependent on the specifics of implementing media, and for that reason will not have evolved. This result has implications for how we rate the near-term possibility of human-like artificial general intelligence, and offers a new way to understand how cognition is rooted, more generally, in biological processes.