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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]

#31

Post by hodgehog11 »

whatever1 wrote: post #27
hodgehog11 wrote: post #17

Earlier quoted context omitted.

Here is some evidence for you then: https://arxiv.org/abs/2411.00566 Not published just yet are experiments for finding solutions to mathematical problems traditionally found with SAT solvers, at much larger scale than was previously possible.

This is just meta heuristic relying on local search :facepalm: You could call it artificial ant colony optimization. People come up with such ideas all the time. Sorry, but nothing groundbreaking here.

Um, okay? Isn't that how most optimisation involving AI is supposed to go?

Perhaps some much needed context. Mathematicians are not stupid; we are very much aware of all the existing forms of genetic optimisation algorithms, cross entropy method, etc. Nothing works on these problems, or at least not well at scale. As I said, state of the art for many of these was SAT-related. The problem is that the heuristic used for exploring new solutions always required very careful consideration as the naive ones rarely worked well.

Here, the transformer is proving effective at searching for good heuristics, far more so than any other existing technique. In this sense, it is achieving far, far. far better performance in optimisation than previous approaches. That is a breakthrough, at least for us mathematicians. If this doesn't constitute improvements in optimisation, I don't know what does.

Saying it's "just meta heuristic relying on local search" is akin to saying these tasks are "just optimisation". If it's so procedural, why weren't we making ground on these things before?

Also, by the way, a :facepalm: is not exactly the pinnacle of academic rebuttal, no matter how wrong I could have been.

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

#32

Post by hodgehog11 »

nybsjytm wrote: post #30
hodgehog11 wrote: post #26

Something else to add is mathematical discovery. There is a team that is very close to solving the Navier-Stokes Millenium Prize problem: https://deepmind.google/discover/blog/discovering-new-soluti... The cynists will comment that I've just been sucked in by the PR. However, I know this team and have been using these techniques for other problems. I know they are so close to a computationally-assisted proof of count…

> I know they are so close to a computationally-assisted proof of counterexample that it is virtually inevitable at this point. That's a strong claim. Is it based on more than the linked work on some model problems from fluid mechanics? I will say that I dread the discourse if it works out, since I don't believe enough people will understand that using a PINN to get new solutions of differential equations has substan…

It's based on knowledge of the related estimates, applying similar techniques to geometric problems, knowledge of all the prior works that lead to the current work, and speaking with members of the team themselves. They are much further along than it appears at first glance. All of the major bottlenecks have fallen; the only concern was whether double precision accuracy is good enough. The team seems to have estimates that are strong enough for this, but obviously keep them close to their chest.

PINNs are different in concept, yes, but clearly no less important, so the additional attention will be appreciated. Asking LLMs for proofs is a different vein of research, often involving Lean. It is much further behind, but still making ground.

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

#34

Post by nybsjytm »

hodgehog11 wrote: post #32
nybsjytm wrote: post #30

Earlier quoted context omitted.

> I know they are so close to a computationally-assisted proof of counterexample that it is virtually inevitable at this point. That's a strong claim. Is it based on more than the linked work on some model problems from fluid mechanics? I will say that I dread the discourse if it works out, since I don't believe enough people will understand that using a PINN to get new solutions of differential equations has substan…

It's based on knowledge of the related estimates, applying similar techniques to geometric problems, knowledge of all the prior works that lead to the current work, and speaking with members of the team themselves. They are much further along than it appears at first glance. All of the major bottlenecks have fallen; the only concern was whether double precision accuracy is good enough. The team seems to have estimate…

> PINNs are different in concept, yes, but clearly no less important

If anything I think they're more important! Whether or not it works out for Navier-Stokes, this kind of thing is an extremely plausible avenue of approach and could yield interesting singularities for other major equations. I am however extremely concerned about public understanding. I know you are well aware that this is worlds away from the speculative technologies like 'mathematical superintelligence' but, if it works out, it'll be like a nuclear bomb of misinformation about AI and math.

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

#35

Post by ants_everywhere »

the__alchemist wrote: post #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…

> 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.

No it wouldn't. I've seen anti-AI people try to make this sort of argument repeatedly and it doesn't make any sense.

It's an attempt to smuggle in an ad-hominem. It's relying on the fact that people who hate AI also hate people who work in AI.

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

#36

Post by ants_everywhere »

hodgehog11 wrote: post #26

Something else to add is mathematical discovery. There is a team that is very close to solving the Navier-Stokes Millenium Prize problem: https://deepmind.google/discover/blog/discovering-new-soluti... The cynists will comment that I've just been sucked in by the PR. However, I know this team and have been using these techniques for other problems. I know they are so close to a computationally-assisted proof of count…

> The cynists will comment that I've just been sucked in by the PR

You can just ignore them. I see a lot of science-literate folks try to meet the anti-science folks as if they're on equal footing and it's almost always a waste of time. Imagine if every time you talked about biology you had to try to address the young earth creationists in the room and try to pre-rebut their concerns.

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

#37

Post by bobmarleybiceps »

hodgehog11 wrote: post #23
NedF wrote: post #15

Awful title, great video. Three points jumped out 1) "really when you look at these machine learning breakthroughs they're probably fewer people than you imagine" In a world of idiots, few people can do great things. 2) External benchmarks forced people upstream to improve We need more of these. 3) "the third of these ingredients research was worth a hundredfold of the first of these ingredients data." Available data…

> We need more of these. > Available data is 0 for most things. I would argue that we need an effective alternative to benchmarks entirely given how hard they are to obtain in scientific disciplines. Classical statistics has gone very far by getting a lot out of limited datasets, and train-test splits are absolutely unnecessary there.

I kind of dislike the benchmarkification of AI for science stuff tbh. I've encountered a LOT of issues with benchmark datasets that just aren't good... In a lot of cases they are fine and necessary, but IMO, the standard for legit "success" in a lot of ML for science applications should basically be "can this model be used to make real scientific or engineering insights, that would have been very difficult and/or impossible without the proposed idea."

Even if this is a super high bar, I think more papers in ML for science should strive to be truly interdisciplinary and include an actual science advancement... Not just "we modify X and get some improvement on a benchmark dataset that may or may not be representative of the problems scientists could actually encounter." The ultimate goal of "ml for science" is science, not really to improve ML methods imo

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

#38

Post by 11101010001100 »

hodgehog11 wrote: post #26

Something else to add is mathematical discovery. There is a team that is very close to solving the Navier-Stokes Millenium Prize problem: https://deepmind.google/discover/blog/discovering-new-soluti... The cynists will comment that I've just been sucked in by the PR. However, I know this team and have been using these techniques for other problems. I know they are so close to a computationally-assisted proof of count…

I think the PR is making it seem that Deepmind is not standing on the shoulder of giants, when in fact it very much is. The paper itself makes this clear. I wish them luck!

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

#39

Post by whatever1 »

hodgehog11 wrote: post #31
whatever1 wrote: post #27

Earlier quoted context omitted.

This is just meta heuristic relying on local search :facepalm: You could call it artificial ant colony optimization. People come up with such ideas all the time. Sorry, but nothing groundbreaking here.

Um, okay? Isn't that how most optimisation involving AI is supposed to go? Perhaps some much needed context. Mathematicians are not stupid; we are very much aware of all the existing forms of genetic optimisation algorithms, cross entropy method, etc. Nothing works on these problems, or at least not well at scale. As I said, state of the art for many of these was SAT-related. The problem is that the heuristic used fo…

Apologies I didn’t mean to be cocky / dismissive.

It’s just that the paper cited is no different than any other paper in the meta-heuristic community.

Some idea for guiding the local search. Some limited sample results. No promises on bounds or generalizability of the method.

If this is ground breaking, then every legitimate meta heuristic paper in the past 50 years was also ground breaking.

I will change my mind if I see a wide set of benchmark results where it consistently beats or is even head-to-head with the SoTA. Then we would know that we have a game changer.

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

#40

Post by bgwalter »

ants_everywhere wrote: post #35
the__alchemist wrote: post #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…

> 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. No it wouldn't. I've seen anti-AI people try to make this sort of argument repeatedly and it doesn't make any sense. It's an attempt to smuggle in an ad-hominem. It's relying on the fact that people who hate AI also hate people who w…

It is not at all an ad hominem. Disclosure of interests and conflicts for interest were assumed to be declared in the open even a decade ago.

Carter sold his peanut farm to avoid conflicts of interest, Trump launched a coin pump & dump on his first day.

If a Nobel Prize winner works for a corporation, that should be disclosed (the original title contained "Nobel Prize Laureate" instead of "DeepMind Director").

But I suppose that in the current age where everyone just wants to get rich these courtesies no longer matter.

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