I’m somewhat curious about how you found these stuff. It would help me (and others reading) to find more good sources to read if you link back the original.
I found the exp—ln thing on twitter (and I’ve seen a fair number of others talk about it).
For bidding games: I think I was either clicking links on the wiki page for Conway’s Soldiers/phutball, which the got me to this article on 1D phutball which I ignored entirely but that made me wonder what this More Games of No Chance book was, which I also basically ignored except that I think I googled the phrase “Games of No Chance” which somehow led me to Games of No Chance. Once more, I basically ignored that, except that I read the description, which says:
...Enthusiasts will find a wide variety of exciting topics, from a trailblazing presentation of scoring to solutions of three piece ending positions of bidding chess. Theories and techniques in many subfields are covered, such as universality, Wythoff Nim variations, misère play, partizan bidding (a.k.a. Richman games), loopy games, and the algebra of placement games. Also included are an updated list of unsolved problems, extremely efficient algorithms for taking and breaking games, a historical exposition of binary numbers and games by David Singmaster, chromatic Nim variations, renormalization for combinatorial games, and a survey of temperature theory by Elwyn Berlekamp, one of the founders of the field.
Most of that sounded kinda boring or stuff I already had on my “stuff to look into sometime” list (I’ve heard of miseré games, and of temperature of games; I haven’t heard the name “loopy games” but I’m pretty sure I’ve seen an example and know what is meant), but I’d never heard of “bidding chess” nor that there was something like renormalization but for games. Renormalization sounds complicated (I haven’t yet learned the original version for quantum field theory!), but bidding chess sounds simple, so I googled that, which led me to the first thing I linked about it.
For the Kolmogorov-Arnord Representation: The elementary function paper linked to a whole bunch of stuff (imo I think they should’ve cut it down—do you really need to link to Napier from the 1600s??), and one of them was this paper on KAR networks as a hope for more interpretable machine learning. The thing that stuck out to me was that Max Tegmark (who I only somewhat recently learned cofounded and leads the Future of Life Institute) wrote it, and the paper originally just looked like an attempt at making breakthroughs in capabilities (whereas now it looks like that it’s at least not the point, even if it seems to me more likely to up capabilities if it works than interpretability).
I’m somewhat curious about how you found these stuff. It would help me (and others reading) to find more good sources to read if you link back the original.
Will try to do so!
I found the exp—ln thing on twitter (and I’ve seen a fair number of others talk about it).
For bidding games: I think I was either clicking links on the wiki page for Conway’s Soldiers/phutball, which the got me to this article on 1D phutball which I ignored entirely but that made me wonder what this More Games of No Chance book was, which I also basically ignored except that I think I googled the phrase “Games of No Chance” which somehow led me to Games of No Chance. Once more, I basically ignored that, except that I read the description, which says:
Most of that sounded kinda boring or stuff I already had on my “stuff to look into sometime” list (I’ve heard of miseré games, and of temperature of games; I haven’t heard the name “loopy games” but I’m pretty sure I’ve seen an example and know what is meant), but I’d never heard of “bidding chess” nor that there was something like renormalization but for games. Renormalization sounds complicated (I haven’t yet learned the original version for quantum field theory!), but bidding chess sounds simple, so I googled that, which led me to the first thing I linked about it.
For the Kolmogorov-Arnord Representation: The elementary function paper linked to a whole bunch of stuff (imo I think they should’ve cut it down—do you really need to link to Napier from the 1600s??), and one of them was this paper on KAR networks as a hope for more interpretable machine learning. The thing that stuck out to me was that Max Tegmark (who I only somewhat recently learned cofounded and leads the Future of Life Institute) wrote it, and the paper originally just looked like an attempt at making breakthroughs in capabilities (whereas now it looks like that it’s at least not the point, even if it seems to me more likely to up capabilities if it works than interpretability).
I don’t know how I got to qutrits.