Hmm it's kinda crazy how well his main points [on why Matt Levine educates so well] map to ML concepts:

1. cases with known outcomes/answers => data with labels

2. first-principles explanations: most people experience an “illusion of depth” => avoiding local minima

3. spaced repetition enabled by fast turnover => stochastic optimization