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The Navier–Stokes Millennium Prize Problem

simonwillison.net

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Re: The Navier–Stokes Millennium Prize Problem

#81

Post by josalhor »

Fordec wrote: post #57
josalhor wrote: post #23

I think this drama was blown up a bit out of proportion. The entire discourse I am seeing online seems to revolve around this: > While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models I mean... yeah? What do you expect? What else can they say? How could you prove a negative in this case? I do not want to comment on specific OAI employee chat messa…

A very simple "these two pipelines don't connect up in our architecture, here's our internal high level network diagram combined with our data ingestion opt-out feature flag that we will stand by in court" as opposed to "yeah, we don't even entirely know how our own customer facing systems are connected to our training pipeline, but it probably didn't happen".

Have the other researchers opted out? On all their accounts? Through the entire time? And did they discuss this with anyone else? And did those people ask ChatGPT stuff? And did they disable it? If I was OpenAI, I would be very careful about my wording here when making claims of "we have never trained on any of their ideas directly or indirectly".

Re: The Navier–Stokes Millennium Prize Problem

#82

Post by feverzsj »

aadyachinubhai wrote: post #17

LLMs can't contribute good code to some of the good OSS math libraries, How is it even solving these problems?

No one knows if it's actually LLM doing the heavy weight. It could be just human written brute force algorithm running on their massive computer cluster.

Re: The Navier–Stokes Millennium Prize Problem

#83

Post by shiandow »

junofan wrote: post #22
sdcfgy wrote: post #14

My take home from this entire drama is that one should not use LLM services for confidential or proprietary information as they all seem to be run by assholes. And you’re sending them everything you are doing. Would you send your lab notebook to an asshole? Hell no. I say that as a mathematician (on paper) who perhaps surprisingly doesn’t give a crap about the problem itself.

Their privacy policy for normie subscribers says in plain English they use your Personal Data for research. I think it’s pretty unreasonable to use the service and expect otherwise.

I think it’s pretty unreasonable to use the service.

Re: The Navier–Stokes Millennium Prize Problem

#84

Post by ghshephard »

npiano wrote: post #78
keremk wrote: post #70

Occam's Razor says: "They heard this problem is solved or about to be solved amongst the rest of the other problems. They prioritized this and put substantial compute with their newest model and solved it." I know everyone loves juicy rumors, theories etc. but honestly that is the simplest and most plausible explanation given the state of AI improvement now. Obviously spending 15 million on a problem is not a slam du…

Why is that simple or plausible? Why is simpler or more plausible than lifting an almost-finished solution from a researcher's account?

Because they solved different problems, and where there was overlap, the solutions look different?

Re: The Navier–Stokes Millennium Prize Problem

#85

Post by grey-area »

Simran-B wrote: post #68

I don't get the sales pitch, spend 15 million dollars to win a 1 million dollar price? Showing of the model's capabilities - okay, but it's not like it solved the problem on its own, and apparently not particularly efficient. Are there practical applications that justify the investment?

The answer to this is obvious: the effect on the multi-billion dollar valuation in the imminent IPO.

Re: The Navier–Stokes Millennium Prize Problem

#86

Post by jansport123 »

adg33 wrote: post #32
bob1029 wrote: post #24

> ... we heard rumors that two Millennium Prize problems had been resolved. Inspired by these rumors ... I've observed this exact effect last week. I made a discovery regarding a stepwise performance improvement in a codebase. I shared the benchmark results with a peer and within 12 hours they replicated the same. We had both been looking for this for years. I think giving someone hope that an answer exists might as…

It's something that happened before LLMs - multiple discovery. Calculus is a classic example.

Yes but in this case, the allegation is Leibniz literally looked into newtons notebooks

Re: The Navier–Stokes Millennium Prize Problem

#87

Post by CSMastermind »

burrish wrote: post #43

>While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models. What do you mean, as OpenAI employee, you cannot tell that his work has entered the training data ? But also correct me if I'm wrong, if the two mathematician were really close to finish this problem, and their conversation were used by OpenAI, shouldn't the Agent have succeeded way faster/e…

Having the chat logs enter the training data and having them have a meaningful influence on the ultimate result the model produces are very different things.

The text for all the Goosebumps books are certainly in the training data and to some small amount influenced the solve. But their contribution was so vanishingly small it would seem absurd to say R L Stein should have recourse for contibuting to the solve.

Re: The Navier–Stokes Millennium Prize Problem

#88

Post by grey-area »

feverzsj wrote: post #30

It could be much worse. OpenAI can easily identify these outstanding human behind their accounts. Human in OpenAI constantly check their logs for breakthrough. When they find something interesting, they brute force the result using their massive computing power. No LLM is even needed.

Or, using anonymised data, search for anyone seriously trying to tackle this problem - probably about 10 people in the entire world and use their ideas as a starting point. They wouldn’t even need to be watching specific accounts or using de-anonymised data if they know what they’re looking for.

Re: The Navier–Stokes Millennium Prize Problem

#89

Post by _bobm »

Hah, what is the infrastructure which takes user sessions (chats with API keys, directions, navier-stokes math/progress) and regurgitates this into pre-training, RL, fine-tuning data? Or better, in-context data?

People talk about the "compute" but what about the "storage"? Is storage exponentially greater, or soon to be, than the compute? Is the storage going to slow down growing to some constant rate, i.e. all people on earth using chatgpt, or no, on the contrary, it will keep growing?

If there were any shady business, I do not condone it, but technologically we are not there yet for said shady business to happen.

Re: The Navier–Stokes Millennium Prize Problem

#90

Post by walrus01 »

sdcfgy wrote: post #14

My take home from this entire drama is that one should not use LLM services for confidential or proprietary information as they all seem to be run by assholes. And you’re sending them everything you are doing. Would you send your lab notebook to an asshole? Hell no. I say that as a mathematician (on paper) who perhaps surprisingly doesn’t give a crap about the problem itself.

> as they all seem to be run by assholes.

Wait until you learn how many other SaaS and web 2.0 and cloud based things are also run by assholes.

You know this metaphor? https://en.wikipedia.org/wiki/Turtles_all_the_way_down

But instead of turtles, it's assholes.

But more seriously, no, none of what I wrote above is an attempt to excuse or play down the specific role of assholes in large AI companies.

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