Seems interesting, thanks!
I definitely think machine learning topics are useful. Given that there's so much stuff out there and you can only cover a small fraction of it, maybe recent machine learning topics are a point of comparative advantage, even. The best textbook on set theory is probably pretty good already.
Another service that could take advantage of pre-existing textbooks is short summaries, designed to give people just enough of a taste to make an informed decision about reading said good textbook. Probably easier than developing a course on algorithmic information theory, or circuit complexity, or whatever.
maybe recent machine learning topics are a point of comparative advantage
Do you mean recent ML topics related to AI safety, or just recent ML topics?
RAISE is already working on the former, it's another course which we internally call "main track". Right now it has the following umbrella topics: Inverse Reinforcement Learning; Iterated Distillation and Amplification; Corrigibility. See https://www.aisafety.info/online-course
Consider not wasting your reader's time with having to register on grasple to be presented with 34-euro paywall.
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Nine months ago we, RAISE, have started creating a Math Prerequisites for AI Safety online course. It has mostly MIRI research related subjects: set theory, computability theory, and logic, but we want to add machine learning related subjects in the future. For 4 months we've been adding new lessons and announcing them on LessWrong. Then we stopped, looked back and decided to improve their usability. That's what we've been busy with since August.
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