Want to wade into the sandy surf of the abyss? 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 so 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.)
That’s really interesting. So the model can generalize the form of what a fact looks like based on these monofacts but ends up basically playing mad libs with the actual subjects. And if I understand the inverse correlation they were describing between hallucination rate and calibration, even their best mechanism to reduce this (which seems to have applied some kind of back-end doubling to the specific monofacts to make the details stand out as much as the structure, I think?) made the model less well-calibrated. Though I’m not entirely sure what “less well-calibrated” amounts to overall. I think they’re saying it should be less effective at predicting the next token overall (more likely to output something nonsensical?) but also less prone to mad libs-style hallucinations.