Want to wade into the snowy 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 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.
(Credit and/or blame to David Gerard for starting this. Merry Christmas, happy Hannukah, and happy holidays in general!)
Yeah, itās not like reviewers can just write āThis paper is utter trash. Score: 2ā unless ML is somehow an even worse field than I previously thought.
They referenced someone who had a paper get rejected from conferences six times, which to me is an indication that their idea just isnāt that good. I donāt mean this as a personal attack; everyone has bad ideas. Itās just that at some point, you just have to cut your losses with a bad idea and instead use your time to develop better ideas.
So I am suspicious that when they say āconstructive feedbackā, they donāt mean āhow do I make this idea goodā but instead āwhat are the magic words that will get my paper accepted into a conferenceā. ML has become a cutthroat publish-or-perish field, after all. It certainly wonāt help that LLMs are effectively trained to glaze the user at all times.