Machine Learning Street Talk (MLST)

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

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Sep 10, 2025
In this enlightening discussion, Professor Karl Friston, a leading neuroscientist and professor known for his pioneering work on the Free Energy Principle, shares his insights into intelligence and consciousness. He delves into the intricacies of epistemic foraging and structure learning, emphasizing the challenges of understanding causal relationships. Friston redefines intelligence, suggesting it transcends biology and includes entities like viruses. The conversation also explores the necessary complexity for consciousness, offering a fascinating glimpse into the future of artificial systems.
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ANECDOTE

Origin Of 'Epistemic Foraging'

  • Keith credits Karl Friston with coining 'epistemic foraging' and Friston confirms it influenced Yoshua Bengio.
  • Friston links epistemic foraging to sensing distant causal forces like electromagnetic fields.
INSIGHT

Free Energy As A Simple Fundamental Principle

  • The Free Energy Principle (FEP) frames living systems as minimizing surprise via conditional probability dynamics.
  • Friston describes it as a principle of least action for conditional densities, simple yet powerful.
INSIGHT

Hierarchy Unlocks Self-Modeling

  • Hierarchical Markov blankets enable self-modeling because active states become sequestered from internal states.
  • This creates recursion where internal states infer both external causes and their own actions, supporting planning-as-inference.
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