Machine Learning Street Talk (MLST) Dr. Thomas Parr - Active Inference Book
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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.
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Seeking Entropy
- Agents seek out entropy by exploring uncertain situations.
- Resolving uncertainty leads to greater confidence and certainty about the world.
Defining Agents
- Active inference defines agents by their separation from the environment, persistence, and dynamic structure.
- The "realness" of an agent is less important than its usefulness as a descriptive tool.
Prediction and Hallucination
- The brain uses prediction to update its internal simulation of the external world.
- When prediction fails to incorporate external input, hallucinations can arise.
