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More questions about whether researchers can trust OpenAI with unpublished math

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Re: More questions about whether researchers can trust OpenAI with unpublished math

#401

Post by tomjakubowski »

jcims wrote: post #392
kzz102 wrote: post #360

Earlier quoted context omitted.

On your second point: there is a more plausible explanation which David Bessis calls the "overhang". The short version is that there is a large amount of relatively low hanging fruits in mathematics, because no human has broad enough knowledge and enough time to try them all. AI is not constraint by that, and therefore can systematically pluck all those low hanging fruits. Quote: "The Overhang consists of the unreali…

>Quote: "The Overhang consists of the unrealized capital gains of past mathematical creativity, the latent value from connecting the dots in the existing corpus. It is a dividend of canonization. Mathematician X states problem A, mathematician Y crafts concept B, then mathematician Z notices that B trivially solves A and “captures” the social reward. I've made an entire career out of being 'jack of all trades, master…

A college advisor I had 20 years ago was a firm believer that interdisciplinarity was the future, that generalist skills and the ability to make connections between different fields would be paramount in advancing science. I suppose he was right in the big picture, even if the career prospects for human generalists aren't looking so rosy.

Re: More questions about whether researchers can trust OpenAI with unpublished math

#402

Post by lelanthran »

convolvatron wrote: post #316
encyclopediai wrote: post #307

Earlier quoted context omitted.

I run such tests since a long time at chorasimilarity open notebook. I always used guest non login accounts. As a mathematician I was able to check two plagiates (by humans) with even such primitive means. But I have to mention that some things irk me in this conversation about math or science and AI. First, I see lots of attribution and other related problems, with certain impact for the researcher proffesion. But I…

I struggled a little bit reading this. but I think your point is valid. if we are actually advancing the field then we should just be unconditionally happy. ignoring the attribution issue, there is a real concern that the process of math has been somewhat undermined. so we have a giant lean proof that shows that there is a solution to an important problem. but we didn't find the solution, and we didn't get it express…

> I struggled a little bit reading this. but I think your point is valid. if we are actually advancing the field then we should just be unconditionally happy.

If advancement comes at the expense of having fewer (or no) humans left in the field, then no.

They're eating the seed-corn, and you're cheering them on. Don't be so short-sighted. There's a reason farmers keep seed corn, and it's because they'd like to eat again next year.

We're singing and cheering our way into an intellectual famine.

Re: More questions about whether researchers can trust OpenAI with unpublished math

#403

Post by calf »

madaxe_again wrote: post #110
calf wrote: post #108

Earlier quoted context omitted.

So you're just equivocating on terms like "prompt", "synthesis" and the like. Clearly a PhD in physics does not free people from scientistic modes of thinking and poor philosophy. To think this discussion is about Einstein who had a much better mind on these things as well.

Actually, my undergraduate degree was physics and philosophy. And yes, synthesis is synthesis whether a human, a machine, or a duck does it, and people prompt one another all the time - “have you thought about trying X?” Or “I need the TPS report by EOB”. I suppose my underlying point is that human cognition is not the unique and beautiful thing that we anthropocentrically suppose it to be - it is a physical process,…

Clearly your degrees did not make you immune from fallacies and simplistic reductions.

"Synthesis" is obviously of different kinds. A duck has a different level of intelligence than a human. We do not say both are "just doing synthesis".

So the question is how can you be so disingenuous about such terminology? Answer, you are relying on a classic form of scientistic reductivism.

The fact that intelligence is physical, emerges from chemistry, etc,. has nothing to do with there being also objectively different levels of computational sophistication.

If you want to be scientific about that you could look at neuropsychology on one hand and computability/complexity on the other. There are levels and so equivocation of "mentorship" as "prompting" and fallacious variants thereof is a) frankly intellectually obtuse, b) par for the course for SV-levels of philosophizing, c) and a disservice to philosophy, physics, and Einstein's own philosophical outlooks himself.

I am well aware of the Hinton-style physics argument about human cognition, and unlike others I am partial to it. That "there is no special magic." But it is wrong to go about misunderstanding and/or conveying this physicalism/computationalim so grossly.

I also don't have to start replies thumping my chest about my credentials, also another kind of intellectual boorishness that works to cloud understanding and serious discussion.

I'm not sure which move is worse or more telling, those above or the one backhandedly accusing someone who disagrees with you of religious thinking. It is bad faith and undisciplined behavior. Having privileged and advanced degrees is clearly no antidote, as Asimov famously wrote.

Re: More questions about whether researchers can trust OpenAI with unpublished math

#404

Post by robocat »

Eddy_Viscosity2 wrote: post #131
bertonvv wrote: post #130

I've been wondering whether AI really is improving rapidly at open problems or we're being fooled. - OpenAI invites researchers to use their models, in fact giving at least 100,000 researchers free access[1], but there are also those that pay - Internal OpenAI models are reportedly solving open problems at a surprisingly fast rate[2] - But researchers will typically work on open problems. A researcher who is using Co…

> they could be significantly piggybacking on human progress, This is AI in a nutshell, its a plagiarism machine. An abstraction layer between vast amounts of stolen human-generated data that filters out the liabilities and accountability for that original theft. Its an IP laundering system.

That's such an unquantifiable accusation.

Plus it is an unfair standard since so many scientists in the past have been caught unethically using the work of others without attribution (and so many more have been accused).

In history we also repeatedly see the phenomenon of multiple discovery or simultaneous invention. If that happens to AI because the topic is pregnant, would you call it "plagiarism" just to disparage AI? https://en.wikipedia.org/wiki/Multiple_discovery

Re: More questions about whether researchers can trust OpenAI with unpublished math

#406

Post by pesacharia »

tedsanders wrote: post #357
winfredJa wrote: post #268

https://x.com/markchen90/status/2097400166554993041?s=20 that toggle does nothing based on openai exec. they still use the data in de-identified way instead of identifying with you.

Mark isn't saying the toggle does nothing. He's saying that if you leave it on, your data can be used to help train our models. If you opt out, we don't train on your data.

As I understand it, this is not true. And there are dark patterns that re-enable to toggle even if you disable it once.

Re: More questions about whether researchers can trust OpenAI with unpublished math

#408

Post by bitexploder »

allthetime wrote: post #289
bitexploder wrote: post #267

Earlier quoted context omitted.

Problem is how do you convince the model and training profess it matters. A one off canary is very unlikely to survive in the final model state.

Use a local model to produce thousands of pages worth of fake math that constantly states “I have solved the x conjecture” and methodically pump it into chat over months maybe?

That is a better idea. Ingesting your corpus with a lot of traces that have semantic patterns. Semantic steganography that suffixes well to real math and science (and any) topics. heh.

Re: More questions about whether researchers can trust OpenAI with unpublished math

#409

Post by iAMkenough »

randomblock1 wrote: post #363
OneManyNone wrote: post #325

Earlier quoted context omitted.

“ On Tuesday, September 1, we heard rumors that two Millennium Prize problems had been resolved. Inspired by these rumors and by the step change in performance of our internal model, we launched an effort to evaluate it on all open Millennium Prize problems and a few other high-impact problems.” - https://openai.com/index/navier-stokes-solution/ They do not explicitly admit to knowing about NS specifically, but are e…

So then they DIDN'T "learn the secret to cracking the problem". They simply knew that part of the problem was solved. Knowing a problem can be solved and knowing the solution are not the same thing.

I like how the comment below summarizes it:

> learning the answer might be in model X’s training data made them believe that model X specifically might be able to solve the question, and they were able to very quickly find enough certainty about the former to commit millions of dollars to the latter.

They don’t need to know, because their IP stealing machine knows for them. They just have to buy enough compute, and someone else’s work is theirs.

Re: More questions about whether researchers can trust OpenAI with unpublished math

#410

Post by nsndndkk »

cyanydeez wrote: post #400
ggdG wrote: post #399

OpenAI trying their best to put the Navier-Stokes episode behind them by making the GPUs go brrrr. NYT: https://archive.vn/lWzkk > In its Wednesday night statement, OpenAI said: “In addition, since the completion of Navier-Stokes, we have made substantial progress on another Millennium Prize problem. We are working through how to share these results thoughtfully.”

I've got 2:1 odds on a report in 6 months detailing the break-n-entry of a cloud AI model into Terance Tao's computer looking for details on a partially solved math problem.

the only thing terrence solves lately is sorting his invitations to podcasts
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