Active inference explained with Prof. Karl Friston

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Published 2021-11-28
📢📢📢 We focus on active inference explained by Prof. Karl Friston the Godfather of Neuroscience. We will also cover: Perceptual Inference, Over-parametrized models, active inference vs. reinforcement learning, etc. Many thanks to Prof. Jamshid Ghasimi (www.linkedin.com/in/jamshid-ghasimi-992a30145/) for helping me design high-quality questions.
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00:00 A brief introduction of Prof. Friston
00:51 What is the Free-Energy Principle?
09:13 Model evidence optimization (can brain OVERFIT?!) and how BRAIN selects the actions with minimum expected surprise!
28:23 The double-descent phenomenon in over-parametrized models (Including our brain) and WHY these models DO NOT overfit?
40:37 Active Inferencs vs. Perceptual Inference and how to they work together for US to LEARN!
52:10 The difference between Active Inference and Reinforcement Learning
01:08:32 How 'Abstract Knowledge' generation (Creativity) in brain can be explained?
01:19:45 The ARCHITECTURE of your Nervous System describes the ENVIRONMENT you are living in!
01:31:48 Will we ever FULLY understand how the brain works and how far have we come?
01:35:00 The Goodbye
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All Comments (11)
  • This is one of the most profound and informative dialogue with Karl Friston..deeply grateful for your stimulating questions
  • @notgaybear5544
    Ive been watching every interview with friston and this is one of the if not the best one.
  • @waclinic9865
    Thank you very much for this amazing interview about the most importand subject
  • @silviopina_111
    35:38 beautiful metaphor of the "mountain range" (genesis of stream becoming a river as it goes downhill). Another lay-person here, loving every time a real life example is made. I second @WP Thank you for posting this!!!
  • @007alg
    Great video, as always, keep it up MLDawn
  • @wp9860
    Thank you for a genuinely delightful discussion. I am a lay person in all the subject matter that relates to the Free Energy Principle (FEP), whether it is physics, machine learning, robotics, thermodynamics, information science, or what have you. I am exploring the topic in an attempt to grasp where science has brought us in answering those age old questions about being, self, free will, etc., that philosophers and theologians have pondered for millennia. Each time I see one of these interdisciplinary discussions with Professor Friston I get new perspectives and improved understanding of the science and the philosophy. In this case, the discussion about over parameterizations finely cleared up in my mind Friston's reference to "sharp minima," which I had heard him mention before. The part discussing the difference between structured learning and FEP was similarly informative. Very well done on those topics and throughout.
  • @MrPronunciation
    Excellent, brother, excellent! Both the content and the idea of such interviews :)
  • @tobiaszb
    It would be easier to look at the equations after watching the human talk. My beliefs about active inference are starting to form.
  • I'm developing an artificial agent based on active inference and epistemic foraging. If anyone would like to help or offer suggestions, I'd like to hear from you.