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Cake day: June 27th, 2023

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  • One area where I don’t know of good recommendations is theoretical computer science. I am not sure what to suggest that would accessibly teach topics like algorithmic/Kolmogorov information theory without sliding downhill into “we can automate the scientific method” crankery. Or, perhaps, which teaches the relevant concepts clearly and solidly enough to make it obvious that LW use of them is crankery.







  • What happened was that I had a handful of articles that I couldn’t find an “official” home for because they were heavy on the kind of pedagogical writing that journals don’t like. Then an acqusitions editor at Springer e-mailed me to ask if I’d do a monograph for them about my research area. (I think they have a big list of who won grants for what and just ask everybody.) I suggested turning my existing articles into textbook chapters, and they agreed. The book is revised versions of the items I already had put on the arXiv, plus some new material I wrote because it was lockdown season and I had nothing else to do. Springer was, I think, the most likely publisher for a niche monograph like that. One of the smaller university presses might also have gone for it.









  • For an exposition of Bayesian probability by people who actually know math, there’s Ten Great Ideas About Chance by Persi Diaconis and Brian Skyrms (Princeton University Press, 2018). And for an interesting slice of the history of the subject, there’s Cheryl Misak’s Frank Ramsey: A Sheer Excess of Powers (Oxford University Press, 2020).

    For quantum physics, one recent offering is Barton Zwiebach’s Mastering Quantum Mechanics: Essentials, Theory, and Applications (MIT Press, 2022). I like the writing style and the structure of it, particularly how it revisits the same topics at escalating levels of sophistication. (I’d skip the Elitzur-Vaidman “bomb tester” thought experiment for reasons.)