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)
oh hey, weāre back to ādeepmind models dreamed up some totally novel structures!ā, but proteins this time! news!
do we want to start a betting pool for how long itāll take 'em to walk this back too?
You think wood glue in your pizza sauce is great? Try prions!
itās weird how theyāre pumping this specific bullshit out now that a common talking point is āwell you canāt say you hate AI, because the non-generative bits do actually useful things like protein foldingā, as if any of us were the ones who chose to market this shit as AI, and also as if previous AI booms werenāt absolutely fucking turgid with grifts too
I suspect itās a bit of a tell that upcoming hype cycles will be focused on biotech. Not that any of these people writing checks have any more of a clue about biotech than they do about computers.
sounds to me a bit like crypto gaming, as in techbros trying to insert themselves as middlemen in a place that already has money, because they realized that they canāt turn profit on their own
That was the hype cycle before crypto - youāll see companies that pivoted from biotech to crypto to AI.
given the semi-known depth of google-lawyer-layering, I suspect this presser got put together a few weeks prior
not that Iām gonna miss an opportunity to enjoy it landing when it does, mind you
Havenāt read the whole thing but I do chuckle at this part from the synopsis of the white paper:
And a corresponding anti-sneer from Yud (xcancel.com):
Now medium-throughput is not a commonly defined term, but itās what DeepMind seems to call 96-well testing, which wikipedia just calls the smallest size of high-throughput screeningābut I guess that sounds less impressive in a synopsis.
Which as I understand it basically boils down to āHundreds of tests! But Once!ā.
Does 100 count as one or many iterations?
Also was all of this not guided by the researchers and not from-first-principles-analyzing-only-3-frames-of-the-video-of-a-falling-apple-and-deducing-the-whole-of-physics path so espoused by Yud?
Also does the paper not claim success for 7 proteins and failure for 1, making it maybe a tad early for claiming I-told-you-so?
Also real-life-complexity-of-myriads-and-myriads-of-protein-and-unforeseen-interactions?
that sound you hear is me pressing X to doubt
Yud in the replies:
āI am so Alpha that the rest of you do not even qualify as Epsilon-Minus Semi-Moronsā
Yud:
Not that curious, apparently
i suspect - i donāt know, but suspect - that itās really leveraging all known protein structures ingested by google and itās cribbing bits from what is known, like alphafold does to a degree. iām not sure how similar are these proteins to something else, or if known interacting proteins have been sequences and/or have had their xrds taken, or if there are many antibodies with known sequences that alphaproteo can crib from, but some of these target proteins have these. actual biologist would have to weigh in. i understand that they make up to 96 candidate proteins, then they test it, but most of the time less and sometimes down to a few, which suggests there are some constraints. (yes this counts as one iteration, theyāre just taking low tens to 96 shots at it.) is google running out of compute? also, theyāre using real life xrd structures of target proteins, which means that 1. theyāre not using alphafold to get these initial target structures, and 2. this is a mildly serious limitation for any new target. and yeah if youāre wondering there are antibodies against that one failed target, and more than one, and not only just as research tools but as approved pharmaceuticals
iām tired boss
wait thatās just antibodies with extra steps
living things literally are just fuzzing it until something sticks and it works
but but proteins! surely theyāve got it right this time! /s
(I wondered what youād say when I saw this. I can only imagine how exhausting)
iām not done with the last one, iāve already collected some footnotes but not enough to my liking