this post was submitted on 25 May 2024
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Did they determine this by comparing what DNA fragments they've managed to recover, or by physical skeletal structure similarities, or what?

I'm no expert in the field, but I just don't see it.

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[–] [email protected] 5 points 5 months ago (9 children)

Sounds about right LOL!

(also am stupid)

[–] [email protected] 12 points 5 months ago (8 children)

we have an obscene amount of fossils sittin around in drawers collecting dust. i cant wait til we can feed all that crap into 3-d scanners, feed it into some detection LLM and vastly expand our knowledge at a rate we are not currently capable.

i read a lot of 'random scientist finds some random fossil in a drawer proving the opposite of some accepted fact'

[–] [email protected] 8 points 5 months ago* (last edited 5 months ago) (6 children)

This exact scenario scares me, because what we know about current LLMs is not that they are good discovers of things, but that they are very convincing liars.

[–] [email protected] 3 points 5 months ago (1 children)

That's because most of what we hear about "AI" is revolving around content "creation" controversies, but these are successfully used in analyzing wide data sets for scientific purposes, like finding new foldings of proteins, diagnosing cancer, reading ancient burned scrolls via etcxrays

[–] [email protected] 2 points 5 months ago

And all of those things are then analyzed and verified before anything is done with them. No reputable scientist is taking those results and dumping it straight into a paper; the deep learning engines are pointing scientists in the right direction; they're taking the haystack and making it a handful. Protein folding is a little different because the results can be directly verified programmatically (I think; I'm not an organic chemist, or biologist, or whoever is doing this research).

The output of LLMs can be great outlines. They can also be wildly, and confidently, wrong.

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