Need to let loose a primal scream without collecting footnotes first? Have a sneer percolating in your system but not enough time/energy to make a whole post about it? Go forth and be mid: 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. Also, happy April Fool’s in advance.)

  • istewart@awful.systemsEnglish
    7·
    21 hours ago

    Just had a video labeled “auto-dubbed” pop up in my YouTube feed for the first time. Not sure if it was chosen by the author or not. Too bad, it looks like a fascinating problem to see explained, but I don’t think I’m going to trust an AI feature that I just saw for the first time to explain it. (And perhaps more crucially, I’m a bit afraid of what anime fans will have to say about this.)

    • YourNetworkIsHaunted@awful.systemsEnglish
      3·
      3 hours ago

      Given the apparent state of the art for autogenerated captions (and by extension the initial challenge of speech recognition) being firmly in the “good enough” range I would not trust the chain of speech recognition -> translation -> text-to-speech. That’s a lot of room for errors to chain, multiply, and obscure themselves through GIGO even if the latter two steps did work as expected.