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 youāll 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 cutānāpaste it into its own post ā thereās no quota for posting and the bar really isnāt that high.
The post Xitter web has spawned soo many āesotericā right wing freaks, but thereās no appropriate sneer-space for them. Iām talking redscare-ish, reality challenged āculture criticsā who write about everything but understand nothing. Iām talking about reply-guys who make the same 6 tweets about the same 3 subjects. Theyāre inescapable at this point, yet I donāt see them mocked (as much as they should be)
Like, there was one dude a while back who insisted that women couldnāt be surgeons because they didnāt believe in the moon or in stars? I think each and every one of these guys is uniquely fucked up and if I canāt escape them, I would love to sneer at them.
(Semi-obligatory thanks to @dgerard for starting this.)
CIDR 2025 is ongoing (Conference on Innovative Data Systems Research). Itās a very good conference in computer science, specifically database research (an equivalent of a journal for non-CS science). And they have a whole session on LLMs called āLLMs ARE THE NEW NO-SQLā
I didnāt have time to read the papers yet, believe me I will, but the abstracts are spicy
(Text2SQL is Not Enough: Unifying AI and Databases with TAG, Biswal et al.)
Hey guys and gals, I have a slightly different conclusion, maybe a baseline 20% correctness is a great reason to not invest a second more of research time into this nonsense? Jesus DB Christ.
Iād also like to shoutout CIDR for setting up a separate āDATABASES AND MLā session, which is an actual research direction with interesting results (e.g. query optimizers powered by an ML model achieving better results than conventional query optimizers). At least actual professionals are not conflating ML with LLMs.