Bert de Vries is Professor in the Signal Processing Systems group at Eindhoven University. His research focuses on the development of intelligent autonomous agents that learn from in-situ interactions with their environment. His research draws inspiration from diverse fields including computational neuroscience, Bayesian machine learning, Active Inference and signal processing. Watch behind the scenes with Bert on Patreon: https://www.patreon.com/posts/bert-de-vries-93230722 https://discord.gg/aNPkGUQtc5 https://twitter.com/MLStreetTalk Bert believes that development of signal processing systems will in the future be largely automated by autonomously operating agents that learn purposeful from situated environmental interactions. Bert received his M.Sc. (1986) and Ph.D. (1991) degrees in Electrical Engineering from Eindhoven University of Technology (TU/e) and the University of Florida, respectively. From 1992 to 1999, he worked as a research scientist at Sarnoff Research Center in Princeton (NJ, USA). Since 1999, he has been employed in the hearing aids industry, both in engineering and managerial positions. De Vries was appointed part-time professor in the Signal Processing Systems Group at TU/e in 2012. Pod version: https://podcasters.spotify.com/pod/show/machinelearningstreettalk/episodes/Prof--BERT-DE-VRIES---ON-ACTIVE-INFERENCE-e2c6l1u Contact: https://twitter.com/bertdv0 https://www.tue.nl/en/research/researchers/bert-de-vries Panel: Dr. Tim Scarfe / Dr. Keith Duggar TOC: [00:00:00] Principle of Least Action [00:05:10] Patreon Teaser [00:05:46] On Friston [00:08:20] Variational Methods [00:17:12] Engineering with Active Inference [00:20:23] Jason Fox [00:20:51] Riddhi Jain Pitliya [00:21:49] Hearing Aids as Adaptive Agents [00:35:46] Main Interview Kick Off, Engineering and Active Inference [00:43:35] Actor / Streaming / Message Passing [00:56:21] Do Agents Lose Flexibility with Maturity? [01:00:50] Language Compression [01:04:37] Marginalisation to Abstraction [01:12:45] Online Structural Learning [01:18:40] Efficiency in Active Inference [01:26:25] SEs become Neuroscientists [01:35:11] Building an Automated Engineer [01:38:58] Robustness and Design vs Grow [01:42:38] RXInfer [01:51:12] Resistance to Active Inference? [01:57:39] Diffusion of Responsibility in a System [02:10:33] Chauvinism in "Understanding" [02:20:08] On Becoming a Bayesian Refs: RXInfer https://biaslab.github.io/rxinfer-website/ Prof. Ariel Caticha https://www.albany.edu/physics/faculty/ariel-caticha Pattern recognition and machine learning (Bishop) https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf Data Analysis: A Bayesian Tutorial (Sivia) https://www.amazon.co.uk/Data-Analysis-Bayesian-Devinderjit-Sivia/dp/0198568320 Probability Theory: The Logic of Science (E. T. Jaynes) https://www.amazon.co.uk/Probability-Theory-Principles-Elementary-Applications/dp/0521592712/ #activeinference #artificialintelligence