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Cake day: July 10th, 2023

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  • Critically, the people who build these machines don’t typically update drivers to port them to a new OS. You buy a piece of heavy equipment, investing tens, or maybe even a hundred thousand dollars, and there’s an OS it works on, maybe two if you’re lucky. The equipment hopefully works for at least 20 years, and basically no OS is going to maintain that kind of compatibility for that long. Linux might get the closest, but I’ll bet you’re compiling/patching your own kernels before 20 years is up.

    This kind of dynamic is unavoidable when equipment vendors sell equipment which has a long usable life (which is good), and don’t invest in software support (which is them being cheap, to an extent), and OSes change enough that these time horizons likely involve compatibility-breaking releases.



  • The USA made it a long way without it being a serious issue, like 200 years. Like presidents would pick qualified federal court judges whose judicial philosophies tended to favor their side a bit more, but were generally good at being fair jurists, and cases decided along the lines of which party’s president had appointed them were super rare.

    Then in the 80s, Reagan started appointing more explicitly partisan judges, and a far right activist think tank started grooming ideologues who were law students as potential future justices, a few of whom Trump ended up appointing. Basically every appointment after 1982 either continued the trend, or worsened it, with the notable exception of Obama appointing Marrick Garland, though he knew there was a good chance the Senate wouldn’t approve any nominee.

    It’s one of those systems that works fine if everybody is acting in good faith, and crumbles when someone tries to take advantage of it. Yeah it’s probably a bad idea.






  • It’s a structural challenge more than a fallacy, but I don’t entirely disagree. This sort of thing works best when one of two things is true, there’s some way for people to organize, or it’s relatively small and there are real options.

    The former clearly isn’t true here, but I think the latter is. There’s a lot of companies trying things with AI, and some are working better or worse. This particular use is relatively small, and I think the downside of doing it is also small in the short term. (This is a giant red flag, avoiding a red flag isn’t a large cost)





  • I suspect there’s a tendency of experts in something to think of people who do it narrowly as people doing at least as much as they are.

    The people who have a bunch of docker services, or complex multi-machine infrastructure are self-hosted software users, and probably in that 1-2% range. People who heard piholes are useful, so they bought a pi 3 and set it up are self-hosted software users. Somebody using an old desktop they got on Facebook marketplace for running Plex media are self-hosted software users… and so on. So are the people in their houses, some of their friends and family.

    Using that inclusive definition, being closer to 10% than 1% makes sense to me.



  • Speed cameras are a privacy issue that doesn’t solve the problem of speeding. People are most comfortable driving the speed the road is designed for, and if that speed is too high, the solution is to modify the road for a safer speed. The speeders in your example are right here, for the wrong reason; speed cameras should be rare if they’re allowed to exist at all. They have, at most, a short term benefit, and broad public surveillance is a very serious issue they contribute to.



  • I was one of the people who went to college to learn things, but the more I learn, the more I’m saddened by all the people I went to school with who studied things they didn’t enjoy, didn’t particularly care to get better at, all because they saw it as a way to make money. In optimizing for money, they miss out on learning and fulfillment.

    This wasn’t that long ago, but I can only imagine how much heavy GenAI use could intensify that effect