The spooks grow ever closer, and the abyss grows ever sandier.

Welcome to the Stubsack, your first port of call for learning fresh Awful you’ll near-instantly regret.

Any awful.systems sub may be subsneered in this subthread, techtakes or no.

If your sneer seems higher quality than you thought, feel free to cut’n’paste it into its own post — there’s no quota for posting and the bar really isn’t that high.

The post Xitter web has spawned soo many “esoteric” right wing freaks, but there’s no appropriate sneer-space for them. I’m talking redscare-ish, reality challenged “culture critics” who write about everything but understand nothing. I’m talking about reply-guys who make the same 6 tweets about the same 3 subjects. They’re inescapable at this point, yet I don’t see them mocked (as much as they should be)

Like, there was one dude a while back who insisted that women couldn’t be surgeons because they didn’t believe in the moon or in stars? I think each and every one of these guys is uniquely fucked up and if I can’t escape them, I would love to sneer at them.

(Credit and/or blame to David Gerard for starting this.)

  • Sailor Sega Saturn@awful.systemsEnglish
    0·
    18 hours ago

    I’m starting to think that simulating the future and past based on a single picture of a falling apple might be a little difficult.

    • Don Piano@feddit.orgEnglish
      0·
      4 hours ago

      Oh, but for a Bayesian super intelligence it’d be easy!

      That’s actually true in a way: Bayes theorem and (actual science-oriented, rather than bullshit handwavey) statistics involving it are about how conditional probabilities interact, including, overly simplified, how to get from prior probabilities (what i find how probable before looking at data) to posterior probabilities (what i find how probable conditioned on data).

      Basically what it means to throw “Bayesian” into the word soup (because a stew requires more substance) is that the fairy tale is not about some blank slate figuring out everything from minimal data and first principles, but that it’s about a model that starts accurately and doesn’t have to adjust much (because otherwise by necessity it’d need more data - otherwise it’s not Bayesian).

      God I hate this

      • Don Piano@feddit.orgEnglish
        0·
        3 hours ago

        Basically: if it’s Bayesian, the less data you put in, the closer you remain to what you started with. It’s not magic.