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.)
LLMs are the Borg, but dumb
https://zeroes.ca/@maleve/114659111863714334
This is a good example of something that I feel like I need to drill at a bit more. I'm pretty sure that this isn't an unexpected behavior or an overfitting of the training data. Rather, given the niche question of "what time zone does this tiny community use?" one relatively successful article in a satirical paper should have an outsized impact on the statistical patterns surrounding those words, and since as far as the model is concerned there is no referent to check against this kind of thing should be expected to keep coming up when specific topics or phrases come up near each other in relatively novel ways. The smaller number of examples gives each one a larger impact on the overall pattern, so it should be entirely unsurprising that one satirical example "poisons" the output this cleanly.
Assuming this is the case, I wonder if it's possible to weaponize it by identifying tokens with low overall reference counts that could be expanded with minimal investment of time. Sort of like Google bombing.
bet https://en.wikipedia.org/wiki/Pravda_network their approach seems to be less directional, initially was supposed to be doing something else (targeting human brains directly) and might have turned out to be a happy accident of sorts for them, but also they ramped up activities around end of 2022
Oh yeah, they'll say absolutely crazy shit about anything that is underrepresented in the training corpus, endlessly remixing what little was previously included therein. This is one reason LLMs are such a plague for cutting-edge science, particularly if any related crackpot nonsense has been snorted up by their owner's web scrapers.
Poisoning would be a piece of cake.