this post was submitted on 01 Sep 2024
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[–] zogwarg@awful.systems 9 points 2 months ago (2 children)

Haven't read the whole thing but I do chuckle at this part from the synopsis of the white paper:

[...] Our results suggest that AlphaProteo can generate binders "ready-to-use" for many research applications using only one round of medium-throughput screening and no further optimization.

And a corresponding anti-sneer from Yud (xcancel.com):

@ESYudkowsky: DeepMind just published AlphaProteo for de novo design of binding proteins. As a reminder, I called this in 2004. And fools said, and still said quite recently, that DM's reported oneshot designs would be impossible even to a superintelligence without many testing iterations.

Now medium-throughput is not a commonly defined term, but it's what DeepMind seems to call 96-well testing, which wikipedia just calls the smallest size of high-throughput screening—but I guess that sounds less impressive in a synopsis.

Which as I understand it basically boils down to "Hundreds of tests! But Once!".
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?

[–] blakestacey@awful.systems 9 points 2 months ago* (last edited 2 months ago) (1 children)

As a reminder, I called this in 2004.

that sound you hear is me pressing X to doubt

Yud in the replies:

The essence of valid futurism is to only make easy calls, not hard ones. It ends up sounding prescient because most can't make the easy calls either.

"I am so Alpha that the rest of you do not even qualify as Epsilon-Minus Semi-Morons"

[–] blakestacey@awful.systems 9 points 2 months ago

Yud:

Curious who besides me predicted it on the record.

Not that curious, apparently

[–] skillissuer@discuss.tchncs.de 5 points 2 months ago

i suspect - i don't know, but suspect - that it's really leveraging all known protein structures ingested by google and it's cribbing bits from what is known, like alphafold does to a degree. i'm 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, they're just taking low tens to 96 shots at it.) is google running out of compute? also, they're using real life xrd structures of target proteins, which means that 1. they're not using alphafold to get these initial target structures, and 2. this is a mildly serious limitation for any new target. and yeah if you're wondering there are antibodies against that one failed target, and more than one, and not only just as research tools but as approved pharmaceuticals