2025-05-09
Moldbug Sold Out - by Scott Alexander - Astral Codex Ten. Because at one point in my life, I read Unqualified Reservations, tried some of the exercises he posted during development of Nock, and bought a share or whatever it was of Urbit. At this point, I have seen Curtis Yarvin speak enough (which means, like, twice) to realize that he’s a buffoon, and I think that Scott Alexander is creating a stronger version of an argument than Yarvin ever actually produced. The gist of Alexander’s argument is that in the “early days” of UR, Yarvin was writing basically political science fiction and developing an argument for a form of corporate autocracy as government, a thought exercise, and that there is a coherent although maybe incomplete narrative and argument there; in recent days, Yarvin is doing the specific things that early-days Yarvin said would be signs that you’ve just got Nazis. I don’t really buy it; Yarvin just writes too much and can’t concisely express a point. That’s kind of why he was once interesting to read — what today looks like LLM slop, looked in earlier years like an intelligent person struggling to get a point across. This argument from Alexander is a Nostradamus effect — with enough slop, you’re guaranteed to find a way to filter it down to something with apparent internal coherency. ^f1d3f6
Computational Mythmaking - by Ben Recht - arg min. Massively interesting comment that computer science was deliberately invented or created as an academic discipline well after computer engineering was developed and in widespread industry use. The idea of computer science as a pure academic pursuit was invented, and the fact that academics may lament the encroachment or connection of industry usually involves some extreme ignorance of the past.
Great opening paragraph:
Academic disciplinary history gets reinvented with each cohort of PhD students. Most people don’t want to be disciplinary historians, so for most scholars “history” ends up being the hodgepodge of inspiring apocryphal tales told in intro classes and related work sections. However, if your discipline matters, it’s vital to seriously engage with its intellectual roots. No academic department arises from the well of intellectual purity. Many have far less noble origins than even computer science. The fathers of statistics all cut their teeth in departments of eugenics. That’s not even being hyperbolic: Ronald Fisher was the chair of the Department of Eugenics at UCL.
Turing was not widely known or cited before 1960. He was cited then as part of deliberate and conscious effort to create an academic discipline around computing:
[ … ] Turing was canonized by the discipline to carve out a sense of intellectual purity in a very applied, service-oriented field.
Haigh asks, “Must theoretical breakthroughs precede and guide practical ones?” I might ask a similar question: Can science be a post-hoc rationalization of technology?
I mean, how could it be anything else? That is science. It is a process for identifying and executing plans to disprove the stories we tell about stuff that happens.
With its embrace of theory, computer science carefully carved out an identity as a pure intellectual exercise closer to mathematics than to business. Don Knuth seems to be one of the central figures in creating this identity.
Maker’s Knowledge by Oliver Reichenstein at iA. Nice essay. People learn by doing and making: although this is an obvious and agreed statement, it should be taken much more literally and much farther than it normally is. Echoes of this even in very abstract problem spaces: in data science, the number one thing is to look at the data, literally look at it Claudia Perlich style, load the data into a spreadsheet and stare at it and explain what you see. Even in mathematics, learning doesn’t happen (for me) until I’ve attempted to teach it — “making” the argument, maybe?