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[00:00:00] Intro
[00:01:36] What we all need to understand about machine learning
[00:06:05] The Master Algorithm Target Audience
[00:09:50] Deeply Connected Algorithms seen from Divergent Frames of Reference
[00:12:49] There is a Master Algorithm; and it's mine!
[00:14:59] The Tribe of Evolution
[00:17:17] Biological Inspirations and Predictive Coding
[00:22:09] Shoe-Horning Gradient Descent
[00:27:12] Sparsity at Training Time vs Prediction Time
[00:30:00] World Models and Predictive Coding
[00:33:24] The Cartoons of System 1 and System 2
[00:40:37] AlphaGo Searching vs Learning
[00:45:56] Discriminative Models evolve into Generative Models
[00:50:36] Generative Models, Predictive Coding, GFlowNets
[00:55:50] Sympathy for a Thousand Brains
[00:59:05] A Spectrum of Tribes
[01:04:29] Causal Structure and Modelling
[01:09:39] Entropy and The Duality of Past vs Future, Knowledge vs Control
[01:16:14] A Discrete Universe?
[01:19:49] And yet continuous models work so well
[01:23:31] Finding a Discretised Theory of Everything
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