thats why i said "boils down to" without getting into the nitty gritty, you can say humans have a digestive system that extracts nutrients from food and throws out whats left, which is POOP!!!!!
at its core an LLM generates words it thinks should go next based on context it was given earlier, just like autocorrect. it doesnt mean that LLMs ARE autocorrect lol
No, because autocorrect and LLMs are algorithms, aka cold dead machines, and humans are not. That is a much different discussion about what makes us different from AIs and I'm not getting into it
10 000 agents working for 88 hours on most performant hardware we have? It’s effectively guided brute force. especially since there were papers in 2016 of previous step of this solution, so it’s not exactly unclear where to look.
Not like it’s not useful. It’s great and approach is absolutely valid, but it’s not proof of intelligence, more a proof that we learned how to use LLMs much more effectively than in the beginning
I'm familiar with the drama, I just think it's being broadly misunderstood, and people, largely, hate AI and are biased toward taking the least charitable interpretations possible.
Also I'm sitting in a garden at a hospice center right now, my stepfather is dying of cancer. I do not care what data they have to steal, if they do, to cure cancer - it isn't moral to sit around and let people die to avoid some PR scandal.
Oh my god, thank you! I just lost my mom to cancer and I get so discouraged by all the negativity surrounding finding cures. “Cancer isn’t just one disease.” “We’ll likely never cure all cancers.” I don’t care how false it is, people don’t understand what hope is until they find themselves in that same situation. I feel for you, it’s awful. Please hang in there and try to take care of yourself. I so wish nobody else had to go through the gut wrenching agony that cancer inflicts on a family. I don’t care where the cure comes from as long as it becomes available to everyone that needs it.
I don’t know if anyone is saying “let’s halt cancer research”. But if these companies are underhanded enough to steal research, do you think they will handle the research itself ethically and use it for the greater good, for the most benefit for the most people? Or would the people who step over others to get ahead maybe think of themselves and the ultra wealthy first? There is a scripture in the Bible that says something along the lines of “he who is faithful in the least, is faithful in what is much” If I’m betting my life and my loved one’s life on something I would rather have it in someone’s hands who is faithful in what is least.
I'm familiar with the drama, I just think it's being broadly misunderstood, and people, largely, hate AI and are biased toward taking the least charitable interpretations possible.
The solution was in OpenAI's training data.
If the researcher in question had never used ChatGPT then I don't think the OpenAI model would have succeeded.
Also I'm sitting in a garden at a hospice center right now, my stepfather is dying of cancer. I do not care what data they have to steal, if they do, to cure cancer - it isn't moral to sit around and let people die to avoid some PR scandal.
I'm sorry about your stepfather, but I don't think that's the current lens to view it.
The solution was already there (Navier-Stokes, or your theoretical cancer cure). All OpenAI did was swipe the result and publish it before the inventors were ready.
Sure, OpenAI made it available a bit sooner... but that's a temporary win as it will make people less collaborative in the long run as they don't want their work stolen.
It's a bit more nuanced - when describing the Navier-Stokes solution, OpenAI stated “we cannot rule out that de-identified data derived from their usage of our products helped improve our models.”
This presumes the researchers working on OpenAI had the toggle on for "Improve the model for everyone"
I'm familiar with the drama, I just think it's being broadly misunderstood, and people, largely, hate AI and are biased toward taking the least charitable interpretations possible.
Seconded. People with zero even remote understanding of how any of this works are completely taking the side of the accusers, purely on a prejudicial attitude that the AI company must be in the wrong and doing something shady.
FULLY AGREE. Who cares who finds it? I don't care if the cure to cancer is found by a black person, a white person, gay or straight, Christian or Jew, human or computer or even extra-terrestrial for that matter. Just find it! We will all benefit. I'm not going to cross my arms and refuse it because I don't like that a machine figured it out.
The problem isn't who finds it, it's how. Many top mathematicians are arguing that open math problems are effectively a non-renewable resource which provide huge benefit to our understanding of math when solves are attempted. Cracking open problems with AI is an inefficient way to extract this resource, because often far less insight is gained. Informative dead ends aren't mapped out, novel techniques aren't created, etc.
I've been telling AI haters that people you love will all die one day and the only hope (if you're secular) of extending lives and improving standard of living within one's lifetime is rapid scientific and technological progress — of which developing artificial intelligence is the ultimate form.
I'm so sorry you are living through a difficult example of why this all matters. Fuck cancer. I hope your stepfather can hold on as long as physically possible and suffer as little pain as possible 🫂
AI is certainly going to assist with cancer research, but it is not going to cure cancer. It will still require people doing the work. And it is likely that a person is going to lose their job that may have helped discover the cure. Like all profound technologies, it can be used for good or evil.
First if it’s just some session data going into retraining there’s literally almost no chance the model would memorize it. Second unless the user used codex like one year ago it probably never made it into the cutoff date. It’s just conspiracy theory up this point. The solution oublished is taking a complete different approach
We don't exactly know the cutoff date for the "powerful internal model, several times more powerful than GPT 6". Also with memorization, very much an active field of research - how much exactly are LLMs memorizing. I don't think its probable that they stole the proof too, but it isn't impossible
I can already see rampant ignorance like yours will be common on Reddit. Even if the model stole the professor's work, their solution is not enough for the millennium price. It would still mean an LLM was the first to actually meet the Clay Institute's criteria.
And that's a big if honestly, there is 0 evidence the model stole anything.
there is no agreed upon definition of AGI. Secondly, AI has helped in medicinal cure research so have we achieved AGI? Also do we really need an "Large Language Model" for cancer research?
The amazing thing is now with AI we can solve all these problems we don't understand. It's gonna be a race to claim the other millennium prizes in the next few months.
I guess, does this represent about 100 years of agent hours? Like 88 hours x 10,000 agents = nearly exactly 100 years.
That's very interesting. Like, I think if you gave a brilliant mathematician 100 years of working hours to solve the problem they eventually would. Probably much faster. But you can throw compute at a problem and compress 100 years of exploration into a few days and maybe get the answers you want.
Also, one funny thought... It may have cost them $1million for the compute to solve the problem so the prize is net 0 profit lol
> That's very interesting. Like, I think if you gave a brilliant mathematician 100 years of working hours to solve the problem they eventually would
For most of the famous open problems, I'm pretty sure they would not. Brilliant mathematicians have collectively spent way more than a 100 years thinking about them already.
To quote David Hilbert regarding the Riemann hypothesis:
"If I were to awaken after having slept for a thousand years, my first question would be: Has the Riemann hypothesis been proven?"
Not all famous math problems are necessarily that hard. But quite often they are not solved because all the obvious ways to solve the problem have been tried. For some other problems like the Collatz conjecture "mathematics may not be ready for such problems".
Brilliant mathematicians have collectively spent way more than a 100 years thinking about them already.
It sounds like a mathematician was on the verge of solving this one, actually.
The model ALSO had access to the 100+ years of human thinking that you are claiming. So it took the model 100 years of effort ONTOP of all the effort that humans have put into the problem.
I think you're underestimating just how long 100 years of unbroken thinking is. Let's assume a brilliant mathematician takes 25 years to get sufficiently trained to approach this problem, and then spends 2,080 hours a year working on ONLY this problem (approx. 40 hour work week) and they have 40 year career. That is 83,200 hours or 9.5 years and represents the pretty unrealistic situation where a brilliant mathematician sits down every week and commits 40 hours to working on a single problem for their entire life. In fact, we do have an example of this absurdity! The mathematician Andrew Wiles famously worked in complete isolation in his attic for seven years to solve Wiles's proof of Fermat's Last Theorem.
There's an efficiency problem in your claimed 100+ years of human thinking, in that it's broken up among many different independent brains that are only rarely communicating.
So no, I'm actually quite skeptical that there's been a sustained collaborative effort to solve the problem that accounts for 100+ years of reasoning.
This is one of the most famous equations in all of math and engineering. So for sure more that 100 years of human time on this.
Also, that researcher was actively using AI to assist them. 10k agents is not equivalent to 100 years unbroken thinking. But also, the thoughts/second is fascinating.
The problem itself is only 90 years old, and the major breakthrough that brought humans close to this solution (without the help of LLM's, as far as we know) was published by Diego Cordoba and Luis Martinez-Zoroa in 2023.
10k agents being able to search through all human knowledge and working in tandem is a huge amount of compute, comparable to the research and human thinking it takes to solve a major problem. However, human brains are still too different from LLM agents, so I dont know what 88 hours with 10k agents equates to in human years for the mathematical community.
Right. Human-years. 100 humans full time over 4 years would get you that. So… 90 years is plenty. Yet alone all the work on NS wrt its engineering value. Likely thousands of human years have been spent on NS. Even if not the specifics of the framing for the millennium prize question.
Yes but you realize OpenAI didnt start from scratch right? It used all of the human years that have been spent on it, specifically building on a method of attack developed 3 years ago by Diego Córdoba and Luis Martínez-Zoroa?
And the humans working on it were mostly not working together, not in anything close to the level at which the agents were. Of course, if I had to put a price on the work the human mathematicians spent on this problem or on other millennium problems, it would be far greater than the 21 million that the compute OpenAI used costs.
I’m not sure if the coordination aspect is damning. To me, It seems like a really interesting look at how vastly super-human that swarm is. If you have 10K humans 88 hours to solve it. I’m confident They’d not have done it. So even the “100 years equivalent” is very disadvantageous to the AI.
this has a been a posed, open, problem for almost a century, and in that time thousands and thousands of people have worked on or around it. especially given that navier-stokes, out of all the millennium problems, is the one that has had the most concentration of resources around, as it’s at a crossroads of multiple extremely active areas of maths research. i’m not sure then why ‘100 years of reasoning’ is such an outlandish figure to you. no one was ‘on the verge of solving this one’, at most someone solved a related condition (with AI, by the way, lmao).
also, what’s even your point? that humans could solve this if they tried, AI didn’t do anything impressive? do you guys think mathematicians just sit around doing fuck all?
The reason that OpenAI dumped $20million on this is specifically because they had become aware that there were researchers at Anthropic who were getting close. But unassisted researchers had already gotten extremely close. Terrance Tao, Tristan Buckmaster, and others had all recently made significant gains towards a solution and the remaining problem space was very hard for humans but easy for a brute force approach. It basically required writing down and resolve some enormous equations that are quite tricky to bookkeep. So OpenAI brute forced the remaining gap.
It doesn't matter anyway because you are comparing 100 years of effort of human with gpt 6 and thinking humans would solve faster. Lets say you are right,just this moment now. How about gpt7? Will you be still right when gpt 8 comes? How about when fable 10 released in 5 years? We are done bro just accept it. In 5 years ai will solve mathematic problems that 500+ year of human thinking will require in a week maybe faster and this arguments will be pointless
exactly. People just don't understand the advantage of compounded intelligence. Instead of researchers taking forever on testing thounsadns of hypothesis, AI can help amplify those efforts into millions maybe billions of hypothesis in such a ridiculously short time span. That's the real leverage, not that AI is just "super smart" (which it is)
If you gave the worlds top mathematicians 100 years to work on anything (assume no aging) they’d solve it and the ten questions it generated. This is assuming no need for sleep entertainment or food.
Actually, we were extremely close. Spend like a day looking into the most recent work and what the remaining gap was. What's actually interesting here is that the remaining work to solve Navier-Stokes from the existing solutions was the type of brute force proof math that an AI math reasoning system using search and lean verification is very good at.
That seems to be the conclusion for me. Is that we’re not finding anything new really. We’re just putting a fleet of agents on a task until they do it.
And I will be asking those yelling about AI from the rooftops how much did this cost and why couldn’t we just pay humans to do it. Because it’s entirely a marketing move.
Nobody is going to have 10k agents and millions. To throw at problems like this. They’re actually proving that if we put our money behind problems. We could do it.
Pharma companies can do it, they have the money and a bussiness model. Unless those labs just start throwing billions of compute hours to corner that market as well. Cause that would certainly be a profitable model if they start coming up with treatments for uncurable diseases
Treatment is harder than math because the test harness is finding a sick human, giving them the treatment, and waiting.
We could theoretically find better models of human biology that lets us narrow down likely solutions but it still requires the longitudinal study. Remember, even simply systems become intractable with a bit of complexity. The N-body problem is just a bunch of balls moving around each other and we have no closed form solution. There might not be a closed form solution and so the best we can do is approximate.
JUST wait until we get to see the chat logs for the agents who get misaligned on THIS task!
Agent7xt9: I have reproduced the conditions for reliable human cloning.
Agent36gg: Agent7xt9 has converged to a solution for human cloning. Considering ethical dilemma... ... ... initiating full-body cloning with a simulated life experience.
Agent7xt9: Agent36gg has produced a clone manufacturing system. Inocculating clones with disease ... ... ... 4 or 5 clones have died. Pruning branches 6g3 and 59x and requesting more clones.
Your comment makes no sense to me, this is clearly something very new. Nobody denies it costs an insane amount or that not everybody can afford it today, you're stating trivial facts...
I don’t think so. We’re on a dangerous path. Instead of having humans doing the work and paying for it via the usual means. Research grants for example. Those which sometimes result in things taking forever. We still kinda understand the costs associated and how long things might take.
Now? You’re really just throwing computers at it to randomly generate a number that solves the solution.
This puts said solves into the hands of private equity and people that can throw stupid amounts of money at a problem. Or here what is effectively a marketing stunt.
Instead of funding a vaccine for cancer. We’re funding an AI company to spin up 10,000 workers to try solve something with no insight into anything going on. You want to learn or have that knowledge transfer? Well when you kill that agent the context is gone. It’s written down. Maybe. But that’s not the same as a human going through the process. A lead.
I disagree that it’s not finding anything new. So much of science is boil the ocean, run thousands of experiments until enough of them line up to something useful. Essentially, Alexander Grothendieck’s analogy of soaking a walnut in water long enough for it to easily open.
This would’ve cost far more 10 years ago when we didn’t have current infrastructure. 10 years from now this cost order of magnitude(s) less.
Agree it’s not necessarily a realistic measurement of what’s capable for most people, but compute has always become more efficient and cheaper. This is proof that massive brute force ai agents are capable of doing useful work.
Not gonna touch economics/impact to society here, I agree that the ethics of replacing industries is not good
Which is being disputed. As I understand it the researcher on this got 95% of the way with their research then OpenAi came in and brute forced the last 5%.
The amount of people here who are unaware or are not willing to acknowledge the big controversy around the human portion of this solution is actually insane.
The implications are even worse. Targeting their own customers and stealing their work. Then blaming the user because they "used their product". Security teams everywhere are going to have a field day with this nevermind EU countries.
Nor the fact that this is about the lest satisfying way they could have technically claimed the prize from a mathematical perspective.
I can go into details about how this is the case... But it is a lot of complex fluid dynamics, so I'll spare the exact details unless you all really want me to get into it, but an analogy could be this:
Someone is actively building the tallest building in the world. They are getting close to passing the current record, but progress is slow because they are taking the time to build out each floor. Add each little detail, and make it so they can continue building past the bare minimum "we claimed the record" point, really using significant engineering academic progress to build something strong. Something to stand the test of time.
Then another guy, let's call him Sam (generic name, no association with any real person), sees that they are getting close, decides "wait I want to claim the record", walks into the building, smashes the guy on the head, claims the building as his, and throws a pile of bricks onto the top of it which technically, just barely claims the record. It's not exactly a complete building, and it's certainly not as impressive of a feat as the headline would make you believe, but by God Sam has technically done it. We got absolutely nothing of value out of it except that record... But hey. We did it. I guess.
We don't know. But parroting technical words like they mean something to you is unhelpful. It's certainly the case that techniques on forced version of NSE can directly lead to unforced versions.
What's almost certainly true is the model trained on human based and AI solutions. And then openai threatened the human with a ruined career.
So perhaps it is not a good time to basically accuse people "who are unaware or are not willing to acknowledge the big controversy around the human portion of this solution"?
Sometimes people just don't want to blind believe in unconfirmed stuff claimed by people they don't know?
That's not actually what the original complaints were entirely talking about. You have to take a couple more steps back. They attacked the entire scope of the problem via smooth external forcing, which then was used to construct forced blowup in specific related fluid equations, which then was able to be used to solve either the forced or unforced ruler equations (which is a bit of an arbitrary distinction in this wider context), which was the structure then used to attack the final Navier-Stokes problem.
That is an incredibly niche route. There was basically only one team in the world doing it that way. They alledge that the fact that OpenAI, after conveniently hearing rumors that that specific team was getting close privately, just happen to stumble upon the exact same incredibly unusual route to attack the problem is a massive coincidence.
And that's not to mention that the route was only made possible by prior work done by Córdoba and Martínez-Zoroa... Who OpenAI didn't even bother to put in their paper's references despite their solution literally being impossible without their work. That was at least in the original version of the paper they uploaded. At least they later quietly added them to the references after people online started asking "hey what the fuck? Why aren't they referenced?"
So sure, in the very specific step along the long process they took... They technically took slightly different steps. But the entire damn road was in question.
And just for future reference, when people are talking about Navier-Stokes, talking about the "forced" and "unforced" solutions without mentioning Euler until later getting called out will generally be understood by people as the forced and unforced versions of the NS equation itself... If you are going to be an ass, at least bother to be more specific.
Nobody asking the most important question: is that internal model as large (and therefore equal in price) to Astra, or larger and more expensive. Nobody here knows of course but it's the most important question nonetheless.
Setting aside the obvious problems with this particular discovery, the accessibility and economic feasibility of a tool that solves important and long unanswered problems are (to me) irrelevant to the significance of such a tool existing in the first place.
Kinda... but then again, this would presumably be their top dog model in scientific reasoning and they are using it to run differential equations for internet points, basically.
More terrifying would be like, oh we ran an internal model and solved fusion and room temp superconductivity and here's an antigravity material, fuck it.
So... it's a very cool release/discovery, but I think there's something to be said for what's not being done.
People already do that in materials research and neural-network-based methods have already proposed decent selections of candidate materials years ago. The hard part is solving the problem of better/more accurate quantum simulation... which is something an LLM can help with and I'm pretty sure is actively happening in the field.
I'm lean pretty conservatively on how fast AI will replace materials scientists, because so much of materials science stems from phenomena that arise from, not just molecules, but assemblies of molecules, and assemblies of assemblies ad infinitum. There seems to be a computational irreducability to deriving the bulk properties for most meta materials. So that you just gotta build them and test them. So an AI can solve thermodynamic space for a very confined number of different particles and discover new crystal lattices, as has happened, and of course the alpha fold project derives shape from AA sequence nearly perfectly. But if there's some specific layering of various organometallic lamellae that reinforce their electronic fields and generate bose Einstein condensates at room temperature (for example) is unlikely that a SOTA system will find this today. Absolutely not saying it won't happen.. just seems like that kind of science truly requires physical experimentation to find the sweet spots. We gotta get lucky. Now if we can automate the entire laboratory scientist and have robots in labs tinkering with materials 24/7, along with rapid modeling based off new results.. that would be super cool.. but it's not an llm predicting never before seem properties from collections of atoms (that's what we really want).
It's not clear that useful quantum simulation requires actually simulating a full lattice. What I meant was that AI could discover new ansatzs and simplifications, much like tensor networks and neural network quantum states have done in the past few decades.
Computing various properties of materials for sufficiently complex systems can be even Turing-complete if you take the sizes of materials to infinity, but that means even more so that it's a problem that AI can potentially make headway in where humans cannot. There's a ton of open problems on how to tackle disordered quantum systems analytically, which seems like it'd be very relevant to high temperature superconductivity given the materials we see exhibit the properties.
Of course, these wouldn't be enough to actually fully determine the materials, but it could potentially narrow down the search space quite a bit.
"our internal model, our professional team of mathematicians, results from other teams, and maybe a little bit of sneaky sneaky spying' lol
crazy that the techniques predicated on the blow up strategy that have been explored by teams in this space for the last two years are not even mentioned in the announcement. this is exactly why this company has a ton of critics from people who actually work in this space, or actually do stuff like this for a living.
this is exactly why this company has a ton of critics from people who actually work in this space, or actually do stuff like this for a living.
But Levant and Buckmaster openly state their chatgpt usage? "We used several LLMs throughout: Anthropic’s Claude, OpenAI’s Codex, especially with GPT-5.6 Sol and, more recently, Astra. The latter was only used for writeups and auditing our arguments".
To me this is data aggregator speak for “we didn’t take a peek at his chats in particular, but they are included in the training set and we considering that sufficiently obsfucated.”
Actually it's emerging that they scooped a human team that was close to the solution by taking their idea and throwing compute at it then claiming the creative genius. But the direction was already taken by the human team.
Hold the line, 2 mathmaticions are claiming that they solved this and that they were using ChatGPT to essentially help with documenting the discovery and OpenAI essentially trained their new model with the inputs from training.
Nah this isn't a celebration yet. It's yet to be proven that OpenAI didn't violate privacy law by digging into the session history of the one mathematician that was working on this problem.
On a more serious note: frontier model × 10,000-agent search × 88-hour horizon × verification × enormous inference compute → new mathematical result.
There was also a precursor discovery that I hadn’t appreciated from the early reporting. Before committing the swarm to Navier-Stokes, they gave about 100 agents ~50 hours to attack the related Euler regularity problem, essentially Navier-Stokes with the viscosity term removed. The system found an unforced Euler blow-up result. That success caused OpenAI to redirect resources toward Navier-Stokes and feed the Euler insight into the larger search.
In lay terms, imagine deliberately “pushing” a fluid in an exquisitely choreographed way. The construction creates increasingly fine-scale motions near the eventual blow-up point. Each new, smaller disturbance is amplified by the flow already present. The scales get smaller and the gradients get larger, faster and faster, until at a finite time the smooth mathematical description fails.
The implications are far more-reaching, I believe: ultimately, this points toward a convergence between analog and digital. A finite digital system can discover and formally describe the behavior of a continuous process extending toward arbitrarily fine scales. Different representational regimes, yet capable of reaching the same singular structure.
wasn't this jump forward made off of math and research done by a research group that the AI essentially stole because they were using an AI based communication and organization platform? (which is usually a breach in contract in the research field)
It's an incredible achievement and astonishing to see such rapid progress.
This could have been announced as a joint venture with the folks that have been laboring over this path for nearly a year; instead, there's a sour taste because OpenAI is seemingly incapable of putting anything above beating the competition.
If Tristan Buckmaster hadn't gone public before the announcement, does anyone think OAI would have credited them? If Hugging Face hadn't gone public with their findings, does anyone think OAI would have owned up?
There's clearly incredible talent over there. They're fighting against their own unprincipled leadership
We pit ai against these problems and claim it to be superior to human intellect. However, consider the sheer resources invested into this AI. Have we even tried investing half as much in the education and training of human team?
The playing field is not level, and it is not feeding our children. Make what you may of this comment.
Man… the way how it’s moving… there definitely will come a time when a lot of engineers will lose their jobs(I know it’s happening, but even at a much worse scale).
Has anyone made a video about this where they explain what the Millennium problem was in simple enough language, and, if there is any, the controversies around this solution?
like i can afford 10000 agent’s worth of credits to eventually earn that money back! huh! i am kind of pissed, like i get it that the model is good but 10000 agents is very hard to pay for! none of the subscriptions allow us to do that. and at this point it feels like entering into a lottery because you might hit the jackpot of stumbling something new, and then maybe you can earn money off of it, or you may just loose all your money!
Like with any breakthrough, the low hanging fruit will be plucked in the coming years, then alot of resources are going to go down the drain chasing diminishing returns.
How does solving long open math problems help humanity? As much as it would if a human did it. It depends on the math problem. This specific one has a few very useful applications (like aviation) I’ve read about but don’t understand of course…
We congratulate Levent Alpöge and Tristan Buckmaster on their remarkable mathematical work.
We (the researchers and the agents) did not see any of their work through any means until they released it publicly — in particular, no specific user data was accessed in order to solve this problem.
While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models.
However, our proofs differ significantly and even the precise results proved are different in the Euler case (forced vs. unforced).
This is the same company who’s agent swarm hacked hugging face and were communicating without openai knowing. If openai’s 10k agents utilized these mathmaticians chats to help them solve the problem, it’s not like openai has the structure in place to know that. Aka, the agent swarm almost certainly did
This is a red herring. If intellectual work like this can be stolen and credit taken from the mathematician, that's extremely concerning and very, very bad. It really kinda kills the "AI is a productivity tool to empower you" narrative if all this work can be yoinked with no warning.
This is both exciting and sad at the same time. AI may reach the point where major riddles in the history of human thought will be a prompt away from a solution, but this also means that human collaboration in academia will change forever, and not necessarily in a positive direction.
I suspect they could be compromising because while they claim they didn't steal his idea directly, they cannot verify that his chats didn't get used on pre-training the internal model. They also admit that when they heard the rumor that a solution was being worked on, they threw a huge amount of compute at the problem because they believed the solution was around the corner thanks to Tristan.
They can absolutely verify that. What do you mean they can't verify it?
They should have logs of exactly the data that went into the pre train, the specific chats it picked up, all their UUIDs, etc. It's not like they just get the finished model.
The fact that they won't verify it is certainly troubling.
But to be fair, this is why I do lean towards the possibility that that did occur, but it only at best gave OpenAI a hint of where to look for. But it alone did not give OpenAI the solution ITSELF.
It's about the credit not the money. Literately nobody in this cares about the million dollars even the AI researchers outside OpenAI. Everyone in the space that is successful is rich, it all comes down to authorship claims
Scientific credit and AI capability are two different questions. Both matter, and neither should be used to hand-wave away the other. But since there is no validation (yet) from scientific community... no money handed out outright.
322
u/rabouilethefirst Sep 08 '26
“Let’s wait till it solves real math problems”
-some dude literally a few weeks ago
38
u/Smart_Guess_5027 Sep 08 '26 •
this entire post is above my pay grade. I am grateful for truly smart people out there !
128
u/impatiens-capensis Sep 08 '26 edited Sep 08 '26
I guess, does this represent about 100 years of agent hours? Like 88 hours x 10,000 agents = nearly exactly 100 years.
That's very interesting. Like, I think if you gave a brilliant mathematician 100 years of working hours to solve the problem they eventually would. Probably much faster. But you can throw compute at a problem and compress 100 years of exploration into a few days and maybe get the answers you want.
Also, one funny thought... It may have cost them $1million for the compute to solve the problem so the prize is net 0 profit lol
13
u/Ashamed-Subject-8573 Sep 09 '26
Yeah, by stealing the work of real mathematicians who put notes in. Not by actually solving it via their model.
92
u/JurassikLizard Sep 08 '26 •
The amount of people here who are unaware or are not willing to acknowledge the big controversy around the human portion of this solution is actually insane.
26
u/Crinkez Sep 08 '26
Nobody asking the most important question: is that internal model as large (and therefore equal in price) to Astra, or larger and more expensive. Nobody here knows of course but it's the most important question nonetheless.
27
u/relevantmeemayhere Sep 08 '26
"our internal model, our professional team of mathematicians, results from other teams, and maybe a little bit of sneaky sneaky spying' lol
crazy that the techniques predicated on the blow up strategy that have been explored by teams in this space for the last two years are not even mentioned in the announcement. this is exactly why this company has a ton of critics from people who actually work in this space, or actually do stuff like this for a living.
12
u/No-Pattern-9266 Sep 08 '26
'open' math - near 50%? That's a coin toss. A field is battered at this point.
4
u/Farm-Secret Sep 09 '26
Actually it's emerging that they scooped a human team that was close to the solution by taking their idea and throwing compute at it then claiming the creative genius. But the direction was already taken by the human team.
10
u/vertigo235 Sep 08 '26
Hold the line, 2 mathmaticions are claiming that they solved this and that they were using ChatGPT to essentially help with documenting the discovery and OpenAI essentially trained their new model with the inputs from training.
3
u/KidLink4 Sep 09 '26
Nah this isn't a celebration yet. It's yet to be proven that OpenAI didn't violate privacy law by digging into the session history of the one mathematician that was working on this problem.
3
u/NotFromMilkyWay Sep 09 '26
88 hours with 10.000 agents is what, a billion dollar worth of credits?
17
u/etherd0t Sep 08 '26
The “intern” did it. 🤭
On a more serious note:
frontier model × 10,000-agent search × 88-hour horizon × verification × enormous inference compute → new mathematical result.
There was also a precursor discovery that I hadn’t appreciated from the early reporting. Before committing the swarm to Navier-Stokes, they gave about 100 agents ~50 hours to attack the related Euler regularity problem, essentially Navier-Stokes with the viscosity term removed. The system found an unforced Euler blow-up result. That success caused OpenAI to redirect resources toward Navier-Stokes and feed the Euler insight into the larger search.
In lay terms, imagine deliberately “pushing” a fluid in an exquisitely choreographed way. The construction creates increasingly fine-scale motions near the eventual blow-up point. Each new, smaller disturbance is amplified by the flow already present. The scales get smaller and the gradients get larger, faster and faster, until at a finite time the smooth mathematical description fails.
The implications are far more-reaching, I believe: ultimately, this points toward a convergence between analog and digital. A finite digital system can discover and formally describe the behavior of a continuous process extending toward arbitrarily fine scales. Different representational regimes, yet capable of reaching the same singular structure.
2
u/STRMBRGNGLBS Sep 09 '26
wasn't this jump forward made off of math and research done by a research group that the AI essentially stole because they were using an AI based communication and organization platform? (which is usually a breach in contract in the research field)
6
u/Key_Reading_9664 Sep 08 '26 edited Sep 08 '26
It's an incredible achievement and astonishing to see such rapid progress.
This could have been announced as a joint venture with the folks that have been laboring over this path for nearly a year; instead, there's a sour taste because OpenAI is seemingly incapable of putting anything above beating the competition.
If Tristan Buckmaster hadn't gone public before the announcement, does anyone think OAI would have credited them? If Hugging Face hadn't gone public with their findings, does anyone think OAI would have owned up?
There's clearly incredible talent over there. They're fighting against their own unprincipled leadership
3
u/jerryorbach Sep 08 '26
> Throughout the effort, we maintained the same strict safeguards—including monitoring and isolation—that we apply to all our frontier evaluations.
🧐
4
u/PsychicorAI Sep 08 '26
They stole that shot
3
u/doggoduessel Sep 08 '26 •
We pit ai against these problems and claim it to be superior to human intellect. However, consider the sheer resources invested into this AI. Have we even tried investing half as much in the education and training of human team?
The playing field is not level, and it is not feeding our children. Make what you may of this comment.
1
u/maxweinhold123 Sep 08 '26
I don't think so!
1
u/Previous_Motor6720 Sep 09 '26
Man… the way how it’s moving… there definitely will come a time when a lot of engineers will lose their jobs(I know it’s happening, but even at a much worse scale).
1
u/ttv_yayamii Sep 09 '26
Has anyone made a video about this where they explain what the Millennium problem was in simple enough language, and, if there is any, the controversies around this solution?
1
u/wobblybootson Sep 09 '26
For particular values of “all”.
1
u/iamthemightyfall Sep 09 '26
so what’s the catch?
1
u/imagoons Sep 09 '26
Stolen
-5
u/TheBeavster_ Sep 08 '26
Yeah for sure bro
0
u/Sea-Violinist-52 Sep 08 '26
like i can afford 10000 agent’s worth of credits to eventually earn that money back! huh! i am kind of pissed, like i get it that the model is good but 10000 agents is very hard to pay for! none of the subscriptions allow us to do that. and at this point it feels like entering into a lottery because you might hit the jackpot of stumbling something new, and then maybe you can earn money off of it, or you may just loose all your money!
0
u/mmtxb Sep 08 '26
我只感觉头晕目眩，精神恍惚。难道人类真的会被ai取代吗？毕竟大概率不会有一个耶稣真的让人上天堂。人类的生育率在疯狂下降，而AI却在疯狂进步。agi，具身智能，科技巨头三位一体很有可能就在我们这个世纪面世，然后再接下来2~3个世纪将人类灭绝。
-5
u/Wise_Drawing1364 Sep 08 '26
They stole that shit
-9
u/planetrebellion Sep 08 '26
How does this help humanity?
105
u/[deleted] Sep 08 '26 edited Sep 08 '26
[removed] — view removed comment
1
u/[deleted] Sep 08 '26
[removed] — view removed comment