Live data from Hacker News

OpenAI fought dirty on career-making math problem

techcrunch.com

31–40 of 64 posts

Re: OpenAI fought dirty on career-making math problem

#31
post #9
post #4

OpenAI has a lot of explaining to do here. The “least worst” representation of the course of events is that their researchers are just jerks, and not behaving in a manner that’s considered acceptable in the research community. Other alleged scenarios just go downhill from there.

It is worth actually reading OpenAI's response, which is basically that they were trying to see if their models could do what Anthropic had already done, and were surprised to discover that (a) Anthropic had not done it at all, and (b) in fact no one else had done it yet. And then they didn't want to give an Anthropic employee coauthor credit for work that OpenAI had done, which idk seems pretty fair?

Their explanation doesn’t help much and there are a few things working against them:

1. This is not the first time they have done these “hey guys check out this breakthrough!” announcements where others quickly came along and say “hey, not so fast.” (Eg Erdos) So, specifically in maths their reputation is not good.

2. They’re blurring the lines between commercial cutthroat developments and the gentlemen’s code of sorts re what’s acceptable in academic research. They were working from material non-public insights into other research, which is why they even tried to poke at this in the way they did. Doing that without collaborating first was a pretty jerk move no mater how you slice it.

3. There’s still lots of open questions about how novel the solution was and the timing here where this “test” only happened after other researchers say they fed OpenAI models at least part of the solution is a little too convenient to gloss over. OpenAI statements here to date on the matter have been rather fuzzy.

All that combined with OpenAI’s less than stellar reputation on ethics is why folks are reacting the way they are right now.

Re: OpenAI fought dirty on career-making math problem

#32
The saddest part of this is no one actually cares about the proof itself.

Does it prove what it claims to prove? Were new mathematics invented? Can this be applied to other areas?

I don’t have a problem with labs solving hard problems if they can, but they could at least pretend to care more about the problems and less about the marketing opportunity.

Re: OpenAI fought dirty on career-making math problem

#33
Setting aside the disagreement, I was very interested to see the net pricing of the discovery:

> All told, the week-long effort consumed 300 billion output tokens — $22.5 million worth of compute, if charged at current Astra rates.

> The Navier-Stokes existence and smoothness problem is one of the seven Millennium Prize problems — a set of major unsolved math problems, each carrying a $1 million bounty

I know openAI isn't solving these problems in order to make profit, but it's interesting to guess how close we are to these things becoming profitable. Eg, if you think their public pricing for Astra is ~2x as expensive as their internal price, then they lost ~10M on net for this proof. That's not profitable, but it is much better than I would have expected, which is exciting for the other Millennium prize problems! Of course the fundamental approach (which they may have plagiarized from Buckmaster and Alpoge) might have added cost to that as well. Nonetheless, I wouldn't be too surprised if they're all solved within the next 3 years!

Re: OpenAI fought dirty on career-making math problem

#34
post #18

Earlier quoted context omitted.

Why is it wasteful to solve one of the most famous problems in modern mathematics? And why would one particular company have no business solving it in the first place?

They brute forced it, that proves they had no business solving it. They didn't know what they were doing and they pumped a bunch more carbon into our atmosphere because hubris basically. Shame on them.

Every sentence in this comment is incorrect

Re: OpenAI fought dirty on career-making math problem

#35
post #8

Shocking, I really expected more from the "totally legitimate startup" planning a $2 trillion IPO with their bottomless money pit. I genuinely assumed that the company credibly accused of stealing from Apple in the most ham-fised way possible would have some kind of guiding ethical principles. At the very least the paragon of decency that is Sam Altman would have stopped this. Get ready, bag-holders on index-tracking…

What index tracking funds will cause investors to lose their shirts? I can't wait to see your short position that will make you rich enough to retire.

You don't remember SpaceX fighting to get fast-tracked on the S&P? Well you are only a day old I suppose.

Re: OpenAI fought dirty on career-making math problem

#37

Who is "Bubeck"? The article doesn't introduce him. Or give his name. Same with "Luis" and "Diego". I am supposing it is https://en.wikipedia.org/wiki/S%C3%A9bastien_Bubeck This is terrible: When Buckmaster pushed to make the dispute public, he says that Bubeck replied: “Why would you ruin your career?” Buckmaster says that when he pushed back, Bubeck followed up with: “If you don’t want me to be nice, then I don’t h…

The report pdf confirms Sebastian was the Bubeck in question

Re: OpenAI fought dirty on career-making math problem

#38
post #31
post #9

Earlier quoted context omitted.

It is worth actually reading OpenAI's response, which is basically that they were trying to see if their models could do what Anthropic had already done, and were surprised to discover that (a) Anthropic had not done it at all, and (b) in fact no one else had done it yet. And then they didn't want to give an Anthropic employee coauthor credit for work that OpenAI had done, which idk seems pretty fair?

Their explanation doesn’t help much and there are a few things working against them: 1. This is not the first time they have done these “hey guys check out this breakthrough!” announcements where others quickly came along and say “hey, not so fast.” (Eg Erdos) So, specifically in maths their reputation is not good. 2. They’re blurring the lines between commercial cutthroat developments and the gentlemen’s code of sor…

RE item 2 -- in lab science, it is entirely normal to have competitive-verging-on-adversarial relationships between labs racing to get results first. Mathematicians apparently need to get used to the idea that math is a lab science now.

And that is a good thing! Competition moves us forward much faster than sitting on results to avoid hurting someone's feelings.

Re: OpenAI fought dirty on career-making math problem

#39

https://mathstodon.xyz/@tao/117237320796901560 Terrence Tao recently published an interesting take that zooms out from the details of the Navier Stokes drama. Its an interesting observation he makes, because it is not dissimilar from the relatively common phenomenon of one academic lab getting scooped by another lab (usually by coincidence).

> one academic lab getting scooped by another lab (usually by coincidence).

I was with you up to “usually by coincidence”.

There’s a long and sordid history in areas of chemistry and areas of biology of holding up a competing paper in review so you can scoop them. I’m sure it exists in physics as well. Certainly biophysics, but probably most subfields.

Often it’s a famous labs that can steamroll review or even just dump the work into PNAS as a “member contribution.”

At least one author of a famous inorganic chemistry textbook was rumored to do this routinely.

And I know of at least one National Academy member who swore off arxiv prepublication after getting scooped.

None of this makes it all right. But plagiarism and academic theft is old and definitely not always accidental.

Re: OpenAI fought dirty on career-making math problem

#40

Setting aside the disagreement, I was very interested to see the net pricing of the discovery: > All told, the week-long effort consumed 300 billion output tokens — $22.5 million worth of compute, if charged at current Astra rates. > The Navier-Stokes existence and smoothness problem is one of the seven Millennium Prize problems — a set of major unsolved math problems, each carrying a $1 million bounty I know openAI…

I would assume they spent similar amounts on the other Millennium problems too. Also, they probably tried it before with older models.
Post reply on HN