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#106 - Prof. KARL FRISTON 3.0 - Collective Intelligence [Special Edition]

Machine Learning Street Talk (MLST)

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Unraveling Markov Blankets and Learning Dynamics

This chapter explores the nature of learning as a gradual process involving inference and belief updating, while examining the pivotal role of Markov blankets in complex systems. It emphasizes the hierarchical interactions of agents, observers, and institutions, focusing on self-organization and the philosophical implications of boundaries in time and space. The discussion ties together structural learning in neural systems and machine learning architectures, highlighting the intricate dynamics that shape understanding within these frameworks.

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