
BI 247 Maxim Raginsky: A Control Theory View on Brains and AI
BI 247 Maxim Raginsky: A Control Theory View on Brains and AI
Brain Inspired
番組の概要欄(原文)
Support the show to get full episodes, full archive, and join the Discord community. The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists. Read more about our partnership. Sign up for Brain Inspired email alerts to be notified every time a new Brain Inspired episode is released. To explore more neuroscience news and perspectives, visit thetransmitter.org. Maxim Raginsky is a professor at the University of Illinois at Urbana-Champaign. Max describes himself as interested in probability and stochastic processes, deterministic and stochastic control, machine learning, optimization, and information theory. Today we mostly lean on his control theory expertise, although you'll here his knowledge is vast in many other domains, even some neuroscience. I wanted his control theory perspective on neuroscience, AI, and biological autonomy, so we dance around a lot of topics related to those. Max also writes a substack called The Art of the Realizable, from which I drew during parts of our conversation. Maxim Raginsky Substack: The Art of the Realizable. Related papers Biological Autonomy Control-related episodes BI 143 Rodolphe Sepulchre: Mixed Feedback Control BI 205 Dmitri Chklovskii: Neurons Are Smarter Than You Think Read the transcript. 0:00 - Intro 3:07 - Low energy lifestyle 4:27 - Engineering and philosophy? 13:52 - Brains vs AI 19:45 - Inferring the inside from behavior 30:57 - Analog vs digital 41:32 - Is the brain a control system? 46:50 - Willems control 1:02:12 - Control vs cybernetics 1:13:26 - A control perspective on AI vs brains 1:17:46 - AGI 1:21:48 - Turing 1950 1:29:07 - Perceptual control theory and active inference 1:40:09 - Passive control in the brain? 1:41:48 - Computation 1:43:36 - Counting spikes