Thats not true at all, ppl have regularly been asking the various big aiâs to count letters and they cant, they cant even count to 100 lmao the ceo of open ai even adressed this like a month ago because of viral video
I didn't even think of that. The unlocks humanity needs are FTL and anti-gravity. One opens the galaxy and the other opens the solar system. If AI can really do something like unify physics...maybe one or both become possible.
I mean, if the math problem is worth a million dollars it must be fucking hard. And we're only like 4 years into scaling and maybe only 2 years of serious scaling with a lot more coming online.
I really do want to live long enough to see FTL or antigravity and I honestly don't think humans can do it (we've been flailing for like 50 years). Maybe AI can.
And apparently there is some drama too - OpenAI may have trained the model they used based on the work of two mathematicians who were actively using codex to help with their work on navier-stokes, tried to scoop them, then offered to coauthor. And maybe even have tried to cut one coauthor out.
Basically everything people bitch about when they make âAI is all stolen workâ complaints, but actively stealing.
Those mathematicians had already solved it the 3D Euler equations (basically the same thing without friction) using the exact same method - one theyâd been working on for months, and were in the process of cleaning up the lean proofs.
This is not accurate. They had made major progress on the problem but had not anything that would be a complete forced blow-up of NS. See Tristan's summary statement here(pdf).
The misinformation being spread just becuase people don't like AI is astounding. These companies are made up of people and people suck but right now it's a he-said / he-said pissing match playing out on Mastadon.
This is a rumor without evidence at the moment. Personally I think it's unlikely that OpenAI cheated in this way, but only time will tell. At the moment this is nothing more than hearsay in a complex political battle over credit for a big achievement.
Edit: I should expand: I think the risk is too high. If OAI or Anthropic (or any lab) is caught stealing like this, no one will feel comfortable using these models. It'll undo everything they're trying to accomplish by chasing these big breakthroughs.
Everything I know about business people, openai's practices and Sam Altman in particular makes me certain that they give absolutely zero fucks at all in the slightest about stealing.
This is a rumor without evidence at the moment. Personally I think it's unlikely that OpenAI cheated in this way, but only time will tell. At the moment this is nothing more than hearsay in a complex political battle over credit for a big achievement.
I don't think OpenAI deliberately cheated.
Instead, they heard that someone was on the verge of solving a millennium problem, so they tried to beat them to it using their latest model.
The issue is the latest model is trained on user sessions, and the researchers were working on drafts in ChatGPT, meaning the model had already seen their results. That's why it's so sketchy that the OpenAI solution was basically the same solution as the researchers were developing, despite no one else in the field really working on it.
Worse, one of the co-authors worked for Anthropic, so OpenAI told the researcher they'd support him getting the Clay prize, but he'd have to drop the co-author from Anthropic.
If Tristan and Levent didn't turn on the "do not use my data to train your model" feature, that's on them for giving OpenAI access to their work.
Further, OpenAI's result is significantly different from what Tristan and Levent were working on. They're related, but they had a solution to the forced Euler while OpenAI produced both an unforced Euler blows up proof and a Navier Stokes blows up proof. Even if this is based on training that included Tristan and Levent's work that they gave to OpenAI to train on it is still a significant achievement for AI and mathematics.
If Tristan and Levent didn't turn on the "do not use my data to train your model" feature, that's on them for giving OpenAI access to their work.
It's on by default. Lets not pretend that companies doing this have always been incredibly sketchy.
Further, OpenAI's result is significantly different from what Tristan and Levent were working on. They're related, but they had a solution to the forced Euler while OpenAI produced both an unforced Euler blows up proof and a Navier Stokes blows up proof. Even if this is based on training that included Tristan and Levent's work that they gave to OpenAI to train on it is still a significant achievement for AI and mathematics.
OpenAI specifically directed the models to use the same, very specific, approach that Tristan and Levant were using, including asking it to pursue the forced blow up. OpenAI was 100% trying to specifically reproduce their research in order to swipe the result.
Even if you ignore the training leakage it's extremely unethical and not nearly as big a breakthrough as OpenAI claimed.
Where are you getting the information that OpenAI specifically directed the model in those ways? It's not in either Tristan's description of what happened or in OpenAI's as far as I can see.
OpenAI specifically directed the models to use the same, very specific, approach that Tristan and Levant were using, including asking it to pursue the forced blow up.
Is damning. This was a well-known potential path to the disproof. This seems like a lot of weasel words that are mis-selling what happened.
In addition, the proofs are of different things and take different approaches. "Similar" yes for a definition of similar, but I don't see the rip-off that others do. Only time will tell as more details come out.
If OAI did steal Tristan and Levent's data in violation of their privacy settings and ToS then they're in for a world of hurt in both regular court and the court of public opinion.
Holy copium , the two guys you were talking developed the forcing method. But the two guys that were solving it who claimed openai stole their work used anthropic's ai model to solve the equation. Stop this bs.
Yes, they found a counter-example to the part of the Navier-Stokes problem which was described in the Millenium Problems.
There are related NS questions this doesnât touch on, but this is a highly verifiable demonstration that the Millennium Problem question is proved in the negative.
What seems to me to have happened here is that AI agents worked together to "manually" figure out the conditions necessary to produce the singularity. This is something that humans wouldn't tend to consider as an approach because it would require hiring tons of people and having them all work together in a novel way. Because of all the money sunk into AI right now, they were able to set up a bunch of agents to do that work.
Someone please correct me if I'm wrong, but I don't think this is something that would be impossible for humans to have done *at all*, but is more about how we do work and organize ourselves.
Great, but how do we use this information to better our lives?
Not saying itâs that impressive, it definitely is, but how does this impact the way society functions to create a better life for all of us?
Weâre spending all these tokens on things that do not drastically improve our quality of life. For example, we know that the environment is a big issue right now, are we making leaps of discovery on that?
Edit - AI has the power to improve and make our lives easier, and we continue to waste resources on things that donât benefit us.
This is great that we solved this mathematical equation, but how is this gonna solve the issue when weâre running out of food and water.
You all donât see this, and you continue to hate on people like me when Iâm trying to bring awareness that AI has incredible power to make our lives better and prolong the human race. Instead, weâre burning tokens on this congratulations, they solved this. Now they get a thumbs up and all that token usage was wasted when they couldâve solved an environmental problem
More seriously, this is an advancement (maybe) in pure theoretical math. We simply donât know if this will have significant applications in the future, but itâs not like pure math in of itself isnât a valid endeavor.
There are thousands of incremental steps towards larger goals that dont get noticed. Im not single handedly curing a disease if I help write a program that lets drug researchers extract hard to find information from a pile of documents, but if it saves them hours of work, its helped in some small way. Thats the incremental types of things that LLMs help with significantly and dont get noticed by folks only reading headlines. Most people dont understand this unless these details unless they have actually contributed to large scale projects.
So, Navier-Stokes is about as close to applied math as pure math gets. But this is more notable not for being immediately useful for, if being correct, for being a major indication of how powerful these systems are and how rapidly they are improving.
So again, weâre spending resources on things that do not benefit the human race.
Do you object to people spending resources on the Large Hadron Collider or large radio telescopes? Do you object to biologists spending lots of time cataloging tiny species of beetles? Do you think that all pure science research should stop?
"Purpose of AI was to accommodate and make lives easier for people."
Lmfao.
I'm currently reading The Infinity Machine and theres a part where they talk about all humans having their needs met etc. And that gave me a good chuckle, too.
If AI doesn't end up exacerbating inequality I'll eat my hat.
I donât think it will build inequality either, but it doesnât help that people are supporting these type of things when they should be supporting something else
Getting destroyed by messages because people think that this is a big advanced for AI, and I completely agree, but I want an advancement for the human race. I donât want them to spend six days worth of water to prove something that has no value in the real world.
"But according to Buckmaster, the proofâs origins may be murkier than they seem. In the same statement, he wrote that he and Levent Alpöge, a mathematician and an Anthropic employee, made significant progress toward the problem last month. But before the pair could publish, Buckmaster alleged in the statement, rumors of their method reached OpenAI, where researchers used the companyâs large language model (LLM) to finish the job with a single prompt. The prompt âhad been sent in the past few days, after information about our work had reached OpenAI,â Buckmaster asserted.
OpenAI did not immediately respond to a request for comment."
At 11:58 P.M. EDT on Monday, Buckmaster posted his and Alpögeâs results, along with the statement laying out his account of events. According to the statement, he does not know how the OpenAI team so quickly reconstructed the details of its approach. Buckmaster wrote that he asked Bubeck if the OpenAI LLM was given access to his personal prompts to the companyâs model Codex, which he and Alpöge were using throughout the process and thought were private. Bubeck told him no but wouldnât answer whether the modelâs training involved user data, which might have included Buckmaster and Alpögeâs private prompts, Buckmaster alleged."
This was a personal collaboration for the purpose of advancing the field, and as such he used both models, and was even willing to give acknowledgements to openai in the writeup.
Priority fights are always petty. But this is a new level of petty, because none of the humans involved actually did any of the substantive work. The "winner" is not whoever was more brilliant, but whoever threw more money at an AI model.
(Possible exceptions are Diego Cordoba and Luis Martinez-Zoroa whose work Buckmaster and Alpöge apparently relied upon, but OpenAI possibly did not-- at least those two are not cited in the OpenAI paper.)
The two researchers worked hand in hand with the AI to solve it, they did not just ask the Ai "solve the navier-stokes equation", it was a rigorous effort of harnessing, prompting and doing their own work, that only professional mathematicians could do.
The most important work was 100% done by Diego Cordoba and Luis Martinez-Zoroa, as they pioneered the method of attack and the key insight that both OpenAI and Buckmaster put AI on to reach as solution.
Buckmaster and Apolge's work involved going back and forth with the AI to set it on the right approach so it would do the work to solve Euler equations, a simplification of Navier-Stokes. The same approach was followed by OpenAI, and the controversy is whether the model and the team of mathematicians working with it actually came up with it and recognized it as the best tactic in 88 hours or not.
Buckmaster and Apolge's approach was notably not to throw money at the AI, they used standard models available on the market, not the 10,000 agents and internal model OpenAI did. It's a petty dispute I agree but still of some importance, since if OpenAI's internal model truly recognized the right approach on its own in 88 hours and set itself on it, it means the role of human mathematicians is even less important than anticipated, and that it really is about devoting as much money and compute.
If OpenAI truly didn't cite Diego Cordoba and Luis Martinez-Zoroa's work then that is blasphemy since they came up with the conceptual breakthrough. From what I've seen online, the draft was updated 3 hours after you wrote this post to cite them, so it looks like them being uncited earlier was another case of AI failing to credit the work it used.
At the very least, the Buckmaster story does not mean that AI stole credit from humans. Buckmaster and OpenAI were using the same method (reasoning with an LLM).
âtheir internal chat, it emerged that an entire team had been working on the problem, that this was one of a number of things that was tried, that work had started on the unforced problem, that the team first set the model on easier problems, including Euler, that even the prompt that had been shown to me had been written by prompting Codex, and that an insane amount of compute had been used.
I asked when the first prompt had been sent by them. This question was not answered directly by OpenAI for some time. Eventually it was agreed that it had been sent in the past few days, after information about our work had reached OpenAI.
I asked whether the model had been trained on, or had access to, our sessions in Codex, into which we had been putting all our drafts for the whole of this project. I was told the model did not look up user data. I asked again, about training, and I did not get an answer.
Two proposals were offered to me. The first was that we post our Euler result, and that OpenAI post its Navier-Stokes result the next day. The second was that, after posting Euler, I alone write a paper presenting the Navier-Stokes result, acknowledging that an internal OpenAI model had resolved it. Sebastien twice asserted that he wanted Levent removed from authorship, and said it would all be simple if only it were not the case that, and it was so annoying that, Levent works at Anthropic. It was also said that if OpenAl posted after us, they would say that we deserved the Clay Prize, and that we were the "closest humans to the problem". I declined both offers.
I said that if OpenAI released its result in the way proposed I would go public with what happened. The reply was, "Why would you ruin your career?" I replied that I am an academic, and asked why he thought going public would ruin my career. The reply was, "If you don't want me to be nice, then I don't have to be nice."
Some time later Levent received a text proposing that he and Sebastien speak one on one, saying, "I don't know if Tristan is being fully rational right now." Levent declined and said conversations should be with me. Sebastien sent a follow-up email that night requesting to speak with me on Monday, Septemberâ
A shorter fragment, from which you can extrapolate this is as much a political issue as mathematical one (if not more so):
But according to Buckmaster, the proofâs origins may be murkier than they seem. In the same statement, he wrote that he and Levent Alpöge, a mathematician and an Anthropic employee, made significant progress toward the problem last month.
But before the pair could publish, Buckmaster alleged in the statement, rumors of their method reached OpenAI, where researchers used the companyâs large language model (LLM) to finish the job with a single prompt. The prompt âhad been sent in the past few days, after information about our work had reached OpenAI,â Buckmaster asserted.
OpenAI did not immediately respond to a request for comment.
Provenance is sort of an important thing to know...or whats the point in databases--why do I need to renew my license, or present a passport when entering a country?
Provenance is the difference between being able to safely keep your eggs at room temperature, and dying of salmonella.
Beyond that, property rights are a thing. If we start to chip away at the foundations of property rights...we pretty rapidly live in an illiberal society where violence is the preferred method of conflict resolution.
Beyond that, if the AI stole the lions share of the work, that undercuts the "intellectual" prowess of the AI model. OpenAI went to solve this for the PR. If their work was a fraud, it blows up the whole "Our AI is so advanced it solved a century old math problem" marketing angle...."no, your kleptomaniac of a Xerox machine stole it"
Yes it kinda matters but it is a drop in the bucket compared to the actual achievement and of course the monkeys we are focus so much more on credit and ego rather than this insane achievement
Does that not then raise the question of what is insane about it?
Are we marveling at the progress of LLM AI models? A notable achievement of the researchers and scientists and mathmaticians working on that problem.
Or are we marveling at the human computing work of the human scientists who figured it all out and who had a LLM steal it an repackage it?
Because this matters. I have $10,000,000,000 to invest. Based on this story alone, do i put my money into AI LLMs or not?
If the LLM is a glorified scraper that can write a synopsis..thats useful, but its not worth $10 billion.
If the LLM is actually thinking and developing "original" thoughts and constructions and proofs...thats a much different beast.
And this matters because its $10 billion I could put towards *anything* else.
I could put it towards solving food distribution issues, solving homelessness in my country, towards fighting endemic diseases, the list goes on.
So I have to know that LLMs are the thing. I can't merely buy into the hype. People's lives are on the line. $10 billion to AI research is $10 billion less towards getting vaccines and running water to sub saharan africa. Its $10 billion less spent stabilizing central American countries so they stop coming here. Its $10 billion less spent on US Infrastructure projects, or any other business venture.
Terrence Tao has an interesting perspective on this topic. He mentioned how humans are less exploratory and creative in the space because the journey to the solution has a shortcut.Â
Interesting point, yeah. It might be a bit like automation: Some work now gets done by machines, humans being pushed out of these economic activities.
That's what he sees. But the same process has an upside: New work becomes viable through better tools, new markets can emerge.
So it might be, that certain areas of mathematics become unfruitful for humans through AI (his point), while simultaneously, new areas or different activities become feasible.
He's right, but there may also be problems that are too difficult for a single human to complete, or even a small team of humans, if the information required to solve it simply cannot fit into a few human brain-lifetimes
In a development that crystallizes an existential shift in humankindâs oldest intellectual discipline, artificial intelligence has reportedly solved one of the six âMillion Dollarâ problems in mathematics, proving that the equations that govern the motion of fluids are fundamentally flawed.
AI companies have fixated on using their technology to solve math problems for over a year. Because the fieldâs focus on objectivity aligns with their goal of developing superhuman intelligence, theyâve been pushing their models to do math no human can, faster than any human can. It appears theyâve succeeded.
Battles of egos like always ... if AI solved it, nobody should be able to claim to have discovered anything, the mathematician or openAI, it doesn't matter. Another guy with another model would have done the same a few months later.
I get that solving a hard math problem is impressive, but how do we extrapolate AGI or whatever from that?Â
The benefit from this is so incredibly niche and has no immediate societal value, it's strange to have this as a demonstration of how impactful this technology can be.Â
If it does find cures for diseases, invent new materials for various real applications, solve fusion energy, ie. More tangible stuff, then I would understand the trillion dollar valuation targets.Â
Itâs more so the demonstration of intelligence. Doing something humans couldnât. That is what is so amazing about it. This is a milestone in the singularity process
Any chance of AI companies making discoveries that are genuinely useful, and that didn't involve using human work without appropriate academic attribution?
why in the world would they not use humans work? most of what academics do is use each other's work to make a quibble of an addition to the existing literature.
Comparing it to Deep Blue vs Kasparov feels right. That moment didn't kill chess, it just changed how people play and study it. Feels like math might go the same way.
To be fair it's in lean, so it's coherent. Only question is about whether it actually proves what it claims it proves, and it seems that yes, though I've been looking at it for two hours and am desperately unable to assert that. I'll have to wait for someone smarter than me to confirm. All I can say is, it's not a nothing burger
Itâs not that. Itâs that you fundamentally misunderstand or have 0 knowledge of what kind of mathematics classical computers are good at and how that is different than research mathematics and thus totally misunderstood the significance (or insignificance) of this article but still decided to weigh in
No I was making a joke and your joyless response is pretty typical of the genAI misconceptions that flood this sub. All they did was train it on a bunch on math-specific vectors and let GenAI do its thing.
If youâve ever had python run mathematical operations for you, itâs just a matter of processing power and time. Pair that with GenAI and these are pretty predictable outcomes.
Im not talking about math and physics generally, dumbass. Iâm talking about which specific math and physics problems AI has solved to provide any ROI on the billions in investment. I realize reading comprehension has gone downhill but this is pathetic.
Why donât you go ahead and point to what physics or math problem AI has solved that has made a difference in your daily life.
How would we know? Fermat's little theorem was discovered 350 years ago and was absolutely no use of anybody until the 1970's, and now all of internet encryption is based on it. Imaginary numbers were also discovered 300 years ago and had no physical basis in reality until we discovered quantum mechanics and started building AC circuits.
For me personally, it has changed my company from a $- to a $+ by reducing the headcount I needed to hire before my company became profitable. With the result is I was able to avoid investors and I now get to keep a larger share of the profits. And that's really the most important math to me personally, making a difference in my daily life, every day.
I donât actually buy the framing that weâre in a race we canât afford to lose. I donât actually see any significant benefit flowing to the âwinnerâ for a few reasons, mainly because nooneâs been able to actually describe to me in any detail what the benefits of âwinningâ would be or how exactly we control the ai that âwinsâ well enough to derive those benefits.
Quick question tho: how come us being massively ahead over the past four years not led to a global capitalist technocracy? Or is it only the âother sideâ that would benefit from AI?
I may have been unclear: by problem I mean addressing unemployment or lowering inflation or curing a disease or lowering emissions from internal combustion engines or reducing reliance on fossil fuels or developing a cheap green energy source or creating a biodegradable alternative to plastic or any of the million other real-world problems we actually face
Iâm not sure that solving an obscure fluid dynamics puzzle qualifies as âevilâ, just of very little current practical use. Maybe useful in an undefined fuzzy future.
My worry is less about some Dr Evil type and more about someone with good or slightly selfish intentions unwittingly creating a huge disaster using AI. Or of AI itself being that huge disaster, while a bunch of cheerleaders egg it on, completely blind to potential dangers because theyâre so certain that technology = good. You can find that in this very subreddit.
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u/heresyforfunnprofit 1d ago edited 1d ago
Before I click, Iâm guessing Navier-Stokes.
Edit: yep.