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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]

#51

Earlier quoted context omitted.

> 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…

Hey! I think I misused words, or was otherwise unclear. Sorry about that. I'm not Anti-AI and don't hate AI or people who work on it. I don't mean to conflate my post with someone who is Anti-AI. No ad-hominem intended.

Hey, sorry I don't mean to imply any of those things about you.

Before commenting I did check out your profile and saw that you weren't AI hater. My intention was the opposite -- I was trying to point out that some arguments don't survive on logic, but on emotional appeal. When enough smart people repeat something, it can slip past our skepticism. But of course my comment was terse and you had no way of knowing that.

In my view, among all people who make claims about what is on the forefront of science or knowledge, the most credible claims come from people whose research is on the forefront of science or knowledge. That's why the claims of experts are considered more credible in their fields than non-experts, even when the non-experts are experts in nearby fields.

So, applying that general rule to this particular case, we would expect the people to most credibly talk about the application of AI to science to be people who know the most about the application of AI to science.

There are other scientists whom I really respect but whose opinions on this particular topic I would find less weighty. For example, Terry Tao is a brilliant mathematician and has consulted on using AI to do research level math. But he was just a few months ago figuring out how to set up ChatGPT with VS Code, so I wouldn't expect him to be the most up to date on how AI is impacting science.

On the other hand, a Nobel laureate who has shown an aptitude for making important scientific discoveries is exactly the sort of person I believe would be able to talk knowledgeably about how to carve up science problems and about how to apply the current generation of AI to solve them. Especially if they've seen the internal world of a company that has a top tier foundational model and a track record for making scientific discoveries. Because in that case they see how science is being done if you have unlimited funds and access to some of the smartest scientists on the planet.

In contrast, I would be much more skeptical of a similar claim made by a company like OpenAI or Microsoft that doesn't have the same track record of producing new science.

For those reasons I don't think it's true that the claim would be more credible from someone with more distance (and hence less expertise). And I think similar claims made in other contexts would strike most people as bizarre. For example, if I said that claims about medicine are more credible if they come from people who aren't medical doctors.

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

#52

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…

They are building a formally-defined counter example to this? Am I understanding correctly?

> In three space dimensions and time, given an initial velocity field, there exists a vector velocity and a scalar pressure field, which are both smooth and globally defined, that solve the Navier–Stokes equations.

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

#53

I'll share something as a former solar researcher. Scientific progress is heavily influenced by how many bodies you can throw at a problem. The more experiments you can run, with more variety and angles the more data you can get, the higher the likelihood of a breakthrough. Several huge scientist are famous not because they are geniuses, but because they are great fundraisers and can have 20/30/50 bodies to throw at…

> But given that LLMs cannot interact with the real world

Pair LLMs with machines and robotics and you are getting closer

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

#54
post #33

I have a mildly psychotic friend who think that he uncovered the secrets to everything with AI. Quantum theory and Jungian archetypes, together with 4 dimensions - great mix

Let's say the "Secrets of the Universe" broadly consists of Graph of 100 "abstract" interconnected concepts. The concepts have to be abstract because it is describing everything. It has to be limited in number because we cannot be endlessly chasing the definitions till we reach the levels of atoms. Is it possible to get glimpse of that Graph just toying with abstract ideas. The exact nodes / concepts used in the graph maybe different (depending on field) but the structure will be isomorphic. It has to be discoverable in any field since we started with the assumption that the Graph is "Secret of the Universe" so it should apply to any subset as well and should be discoverable from that subset. This is like analytic functions where knowing its derivatives in a small enough interval can lead us to the exact function.

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

#55

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…

If it was a sure thing, why publish the paper they did? Why not just solve NS?

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

#56

I'll share something as a former solar researcher. Scientific progress is heavily influenced by how many bodies you can throw at a problem. The more experiments you can run, with more variety and angles the more data you can get, the higher the likelihood of a breakthrough. Several huge scientist are famous not because they are geniuses, but because they are great fundraisers and can have 20/30/50 bodies to throw at…

Seems you're burying the Lede in your post - yes, AIs aren't scientists.

What can be said about scientists and bodies is interesting but ultimately irrelevant.

Edit: I'd add that various LLMs/neural-nets have turned out to be great tools for research. I simply find the scientist-equivalent position problematic.

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

#57

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…

I don't understand how a scientist being awarded a Nobel prize in their field, using AI, does not add to AI's credibility as a useful tool?

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

#58

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…

If it was a sure thing, why publish the paper they did? Why not just solve NS?

It will take another few months at least, and the rest of the argument will comprise a fair few pages. But the hardest part is over.

When working toward a problem of this magnitude, it is natural to release papers stepwise to report progress toward the solution. Perelman did the same for the Poincare conjecture. Folks knew the problem was near a solution once the monotonicity proof of the W functional came out.

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

#59
post #52

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…

They are building a formally-defined counter example to this? Am I understanding correctly? > In three space dimensions and time, given an initial velocity field, there exists a vector velocity and a scalar pressure field, which are both smooth and globally defined, that solve the Navier–Stokes equations.

They find a very good approximate blowup solution (non-smooth) using a NN. When the solution is good enough, you just need careful fixed point theory to infer an actual solution.

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

#60

I'll share something as a former solar researcher. Scientific progress is heavily influenced by how many bodies you can throw at a problem. The more experiments you can run, with more variety and angles the more data you can get, the higher the likelihood of a breakthrough. Several huge scientist are famous not because they are geniuses, but because they are great fundraisers and can have 20/30/50 bodies to throw at…

> But given that LLMs cannot interact with the real world What type of interaction do you envision? Could a non-domain-expert, but somewhat trained person provide a bridge? If the LLM comes up with the big ideas and tells a human technical assistant to execute (put the vial here, run the 3D printer with this file, put the object there, drive in a screw), would that help? But dexterous robots are getting more and more…

> If the LLM comes up with the big ideas and tells a human technical assistant to execute (put the vial here, run the 3D printer with this file, put the object there, drive in a screw), would that help?

No, because the bottleneck isn't the thinking but running experiments.

I worked in solar research, assembling a cell to test implied 40 different steps and from beginning to testing it was around 4 to 5 days.

This means that in one year working full time I will realistically run 40ish different experiments. Many of those will need to be done multiple times, and when you have 40 different steps that can go wrong and kill your efficiency this further compounds.

Thus realistically are running 5 to 10 different experiments (or better, a handful plus their variations).

At no point in this process you're like "yeah, if only LLMs could provide ideas", it's just not true, you get millions of ideas, time and bodies are the limit.

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