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Machine Learning Street Talk (MLST)

Dr. Thomas Parr - Active Inference Book

May 1, 2024
Join Dr. Thomas Parr, a postdoctoral scholar at the Wellcome Centre for Human Neuroimaging, as he delves into the fascinating world of active inference. He explores how living systems resist entropy and navigate their environments through a mathematical framework. Parr discusses the evolution of neural networks and contrasts traditional AI with active inference's potential for deeper world modeling. He also navigates complex topics like agency, consciousness, and the collaborative journey of writing his book on these intricate concepts.
01:37:09

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Podcast summary created with Snipd AI

Quick takeaways

  • Active Inference unifies physics, biology, and psychology to explore agency and causality.
  • The dual perspective of Active Inference involves holistic resistance to entropy and mathematical Bayesian mechanics.

Deep dives

Active Inference: A Comprehensive Overview

Active Inference, as discussed in the podcast, delves into two key perspectives: the high road and the low road. The high road offers a holistic view, emphasizing how organisms resist entropic forces by minimizing free energy. In contrast, the low road delves into the mathematical aspects, exploring Bayesian mechanics, variational inference, and treating perception as perceptual inference. This dual approach converges to highlight the role of action in perception and planning within active inference.

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