DR. JEFF BECK - THE BAYESIAN BRAIN

An episode of the Machine Learning Street Talk (MLST) podcast, hosted by Machine Learning Street Talk (MLST), titled "DR. JEFF BECK - THE BAYESIAN BRAIN" was published on October 16, 2023 and runs 70 minutes.

October 16, 2023 ·70m · Machine Learning Street Talk (MLST)

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Summary

Support us! https://www.patreon.com/mlst MLST Discord: https://discord.gg/aNPkGUQtc5 YT version: https://www.youtube.com/watch?v=c4praCiy9qU Dr. Jeff Beck is a computational neuroscientist studying probabilistic reasoning (decision making under uncertainty) in humans and animals with emphasis on neural representations of uncertainty and cortical implementations of probabilistic inference and learning. His line of research incorporates information theoretic and hierarchical statistical analysis of neural and behavioural data as well as reinforcement learning and active inference. https://www.linkedin.com/in/jeff-beck... https://scholar.google.com/citations?... Interviewer: Dr. Tim Scarfe TOC 00:00:00 Intro 00:00:51 Bayesian / Knowledge 00:14:57 Active inference 00:18:58 Mediation 00:23:44 Philosophy of mind / science 00:29:25 Optimisation 00:42:54 Emergence 00:56:38 Steering emergent systems 01:04:31 Work plan 01:06:06 Representations/Core knowledge #activeinference

Episode Description

Support us! https://www.patreon.com/mlst

MLST Discord: https://discord.gg/aNPkGUQtc5

YT version: https://www.youtube.com/watch?v=c4praCiy9qU

Dr. Jeff Beck is a computational neuroscientist studying probabilistic reasoning (decision making under uncertainty) in humans and animals with emphasis on neural representations of uncertainty and cortical implementations of probabilistic inference and learning. His line of research incorporates information theoretic and hierarchical statistical analysis of neural and behavioural data as well as reinforcement learning and active inference.

https://www.linkedin.com/in/jeff-beck...

https://scholar.google.com/citations?...

Interviewer: Dr. Tim Scarfe

TOC

00:00:00 Intro

00:00:51 Bayesian / Knowledge

00:14:57 Active inference

00:18:58 Mediation

00:23:44 Philosophy of mind / science

00:29:25 Optimisation

00:42:54 Emergence

00:56:38 Steering emergent systems

01:04:31 Work plan

01:06:06 Representations/Core knowledge

#activeinference

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