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John Jumper: AI is revolutionizing scientific discovery [video]

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Re: John Jumper: AI is revolutionizing scientific discovery [video]

#2
First jump that computers gave us : speed. With excess of speed came the ability to brute force many problems.

Next jump given by AI (not LLMs specifically, I mean “machine learned systems” in general) is navigation. Even with large amounts of speed some problems are still impractically large, we are using AI to better explore that space, by navigating it smarter, rather than just speeding through it combinatorially.

Re: John Jumper: AI is revolutionizing scientific discovery [video]

#8
NVIDIA published the Illustrated Evo2 a few days ago, walking through the architecture of their genetics foundation model:

https://research.nvidia.com/labs/dbr/blog/illustrated-evo2/

It's nice to see more and more labs using ai for drug discovery, something truly net positive for society.

Re: John Jumper: AI is revolutionizing scientific discovery [video]

#9
I am reposting something along the lines of a flagged and dead comment: This would be lend more credibility to the premise AI is revolutionizing scientific discovery if it came from someone who's Nobel (or work in general) were in a non-AI-centered domain. This is not a critique of his speech or points, but I think the lead implied by the (especially Youtube) title would hit harder if it came from someone whose work wasn't AI-centered.

Jumper's work is the poster child of AI success in science; this isn't about a new domain being revolutionized by it.

I will throw out an idea I've been thinking about recently about a far less ambitious idea, but related: Amber (MD package) provides Force Field names and partial charges for a number of small organic molecules in their GeoStd set. I believe these come from its Antechamber program. Would it be possible to infer useful FF name and Partial charge for arbitrary organic molecules using AI instead, trained on the GeoStd set data?

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