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Karl Friston - Why Intelligence Can't Get Too Large (Goldilocks principle)

Machine Learning Street Talk (MLST)

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Exploring Epistemic Foraging and Structure Learning

This chapter explores the concept of epistemic foraging, examining how individuals gather knowledge amidst complex causal relationships in the universe. It highlights the challenges of understanding cause-effect modeling in human cognition compared to simpler organisms and emphasizes the need for improved mathematical frameworks for structure learning.

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