Dynamics of Bayesian Inference
Friston reveals how systems with a Markov blanket gravitate towards a pullback attractor, maintaining coherence and identity. The concept of bayesian active inference suggests that systems encode beliefs to make decisions and update based on outcomes, bridging the gap between abstract inference and physical laws. The free energy principle applies universally, hinting at a mathematics of emergence and consciousness.In this clip
From this podcast
Machine Learning Street Talk (MLST)
#106 - Prof. KARL FRISTON 3.0 - Collective Intelligence [Special Edition]
Related Questions
How do self-organizing systems work as discussed in the episode Karl Friston: Neuroscience and the Free Energy Principle | Lex Fridman Podcast #99 and the clip Markov Blanket Dynamics?
How do self-organizing systems work as discussed in the episode Mindscape 87 | Karl Friston on Brains, Predictions, and Free Energy and the clip Dynamic System Exploration, as well as in the episode Karl Friston: Neuroscience and the Free Energy Principle | Lex Fridman Podcast #99 and the clip Markov Blanket Dynamics?
Can chaos lead to spontaneous order in the context of the episode #106 - Prof. KARL FRISTON 3.0 - Collective Intelligence \[Special Edition] and the clip Dynamics of Bayesian Inference?