Earlier quoted context omitted.
The math is all that matters.
A hundred pages of impenetrable brute forced Lean would advance the field much less than something elegant and human understandable, perhaps relying on some new clever spark of innovation that might inspire new areas of research. Particularly if the first proof being "solved" thanks to piles of money and compute for self-serving marketing discourages the mathematician who might have otherwise devoted years of focus t…
Navier-Stokes – Tristan Buckmaster [pdf]
421–430 of 862 posts
Re: Navier-Stokes – Tristan Buckmaster [pdf]
#422From OpenAI: > While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models This is the crux of it. If Tristan's work and insights were not used to train OpenAI models, then this just looks like a case of hyper-competitive academic sniping that has been going on for decades (check out Watson and Crick!) accelerated by AI as a tool. The fact that this is…
If they could declare with certainty that Buckminster's and Alpoge's usage data had been totally excluded from training, would that set a worse precedent and reflect poorly on their de-identification process (and data access safeguards moreover)? This may sound like a charitable interpretation of OpenAI's remark, but consider that the lie would be (I think) impossible to falsify from the outside. They could easily ju…
> If they could declare with certainty that Buckminster's and Alpoge's usage data had been totally excluded from training, would that set a worse precedent and reflect poorly on their de-identification process (and data access safeguards moreover)?
No; if they said "we can see that Tristan opted out of model improvement, therefore we are confident his work and ideas did not improve our model," that would be an excellent and reassuring precedent.
Re: Navier-Stokes – Tristan Buckmaster [pdf]
#423From OpenAI: > While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models This is the crux of it. If Tristan's work and insights were not used to train OpenAI models, then this just looks like a case of hyper-competitive academic sniping that has been going on for decades (check out Watson and Crick!) accelerated by AI as a tool. The fact that this is…
If he didn't opt out I'm not sure I'd agree that it was fair game.
I'm pretty sure it would be considered plagiary amongst colleagues and it is a terrible precedent if we just let OpenAI steal any good idea they can get their hands on if they think it is profitable. You'd effectively sign away any and all rights to anything built with AI if OpenAI chooses to reengineer it before you.
Re: Navier-Stokes – Tristan Buckmaster [pdf]
#424From OpenAI: > While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models This is the crux of it. If Tristan's work and insights were not used to train OpenAI models, then this just looks like a case of hyper-competitive academic sniping that has been going on for decades (check out Watson and Crick!) accelerated by AI as a tool. The fact that this is…
If such a thing can happen (a major breakthrough in a chat makes it into the retrain of the week and then the first one who asks about it gets it) I wonder if this is not the first instance if it happening, seeing the row of Erdos problems, Jacobian conjecture, maximum bound distance between primes, Riemann Hypothesis (literally a dude insisting on the chat), etc...
Re: Navier-Stokes – Tristan Buckmaster [pdf]
#425Earlier quoted context omitted.
It's specifically the last two bullet poitns - Tristan is suspicious of the timing, as only few others were trying this approach. OpenAI says the model didn't access his user data directly, but leaves unanswered whether Tristan's chat conversations were part of the training. - OpenAI says they would partially credit Tristan for the $1,000,000 discovery (even though Tristan did not solve the $1,000,000 problem) — but…
Both Sam Altman and Sebastien Bubeck admitted they only want Buckmaster to be the lead author on a rewrite of the OpenAI proof. https://x.com/sama/status/2097385167002415140 https://x.com/SebastienBubeck/status/2097379411691516310 A wake up call for using OpenAI models. If you discover something with their model and you work for a competitor, they “felt it would be inappropriate” for you “to author OpenAI’s work”.
These responses seem to me to make it abundantly clear who's telling the truth here. I wonder who this fools.
It would be extraordinarily easy to simply say, this model was not trained on your work, if that were the case.
It's telling that they refuse to acknowledge the root issue here, and are attempting to shift the conversation elsewhere.
Re: Navier-Stokes – Tristan Buckmaster [pdf]
#426From OpenAI: > While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models This is the crux of it. If Tristan's work and insights were not used to train OpenAI models, then this just looks like a case of hyper-competitive academic sniping that has been going on for decades (check out Watson and Crick!) accelerated by AI as a tool. The fact that this is…
If he didn't opt out I'm not sure I'd agree that it was fair game. I'm pretty sure it would be considered plagiary amongst colleagues and it is a terrible precedent if we just let OpenAI steal any good idea they can get their hands on if they think it is profitable. You'd effectively sign away any and all rights to anything built with AI if OpenAI chooses to reengineer it before you.
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Re: Navier-Stokes – Tristan Buckmaster [pdf]
#427Earlier quoted context omitted.
If they could declare with certainty that Buckminster's and Alpoge's usage data had been totally excluded from training, would that set a worse precedent and reflect poorly on their de-identification process (and data access safeguards moreover)? This may sound like a charitable interpretation of OpenAI's remark, but consider that the lie would be (I think) impossible to falsify from the outside. They could easily ju…
> If they could declare with certainty that Buckminster's and Alpoge's usage data had been totally excluded from training, would that set a worse precedent and reflect poorly on their de-identification process (and data access safeguards moreover)? No; if they said "we can see that Tristan opted out of model improvement, therefore we are confident his work and ideas did not improve our model," that would be an excell…
It seems like Tristan did not opt out of model improvement (he would say so if he did), so what can they possibly say now?
Re: Navier-Stokes – Tristan Buckmaster [pdf]
#428Earlier quoted context omitted.
If they could declare with certainty that Buckminster's and Alpoge's usage data had been totally excluded from training, would that set a worse precedent and reflect poorly on their de-identification process (and data access safeguards moreover)? This may sound like a charitable interpretation of OpenAI's remark, but consider that the lie would be (I think) impossible to falsify from the outside. They could easily ju…
> If they could declare with certainty that Buckminster's and Alpoge's usage data had been totally excluded from training, would that set a worse precedent and reflect poorly on their de-identification process (and data access safeguards moreover)? No; if they said "we can see that Tristan opted out of model improvement, therefore we are confident his work and ideas did not improve our model," that would be an excell…
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Re: Navier-Stokes – Tristan Buckmaster [pdf]
#429Earlier quoted context omitted.
This seems unsupported. OpenAI has access to internal models that the general public doesn't have and a compute budget that dwarfs what an NYU professor would have.
it's very possible they only had to use the massive compute budget because they were trying to plagiarize his work before he published it though, e.g. autonomously do things in ~7 days what he had likely been thinking about for ~1 year.
This doesn't really make sense. You don't need massive amounts of computing to plagiarize something.
The most nefarious explanation seems to be that they got wind it was possible to solve NS via LLMs and perhaps a small nudge in the right direction.
Re: Navier-Stokes – Tristan Buckmaster [pdf]
#430From OpenAI: > While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models This is the crux of it. If Tristan's work and insights were not used to train OpenAI models, then this just looks like a case of hyper-competitive academic sniping that has been going on for decades (check out Watson and Crick!) accelerated by AI as a tool. The fact that this is…
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