I think the author is not aware of how much the Millennium Prize proof was actually driven by a human working for years towards that problem. The AI did not solve this on its own. A world class mathematician prompted it towards the proof. In my view, this is still a human achievement, not an AI achievement.<p>If I design a bulldozer to push a five ton rock, did I push the rock or the bulldozer?
> If I design a bulldozer to push a five ton rock, did I push the rock or the bulldozer?<p>Unequivocally the bulldozer. You get to take the blame in design of the bulldozer, though.
The law (which is supposed to codify the common sense and shared values underpinning a society—note "supposed to") disagrees with you: if I use a bulldozer to damage your property, you can sue me, not the bulldozer or its maker.
You could say that about every scientific/mathematical breakthrough. Einstein's Special relativity depended heavily on Lorentz's work, the Michelson-Morley experiments, Maxwell's equations. Grigori Perelman, the only person to have solved a Millenium Prize problem, noted how his work was only possible due to Richard S. Hamilton's work on Ricci flow.<p>Most scientific breakthroughs are just the completing the last 5% of work already done, but that last 5% is very hard and still only happens very rarely. That an AI was able to synthesize all the work and bring it forward is evidence that AI can make novel progress on the same level as renown mathematicians.
Einstein literally stated he was not influenced by the Michelson-Morley experiments, but it's a common myth that he was.<p>"When Ι asked him how he had learned of the Michelson Morley experiment, he told me that he had become aware of it through writings of Η. Α. Lοrentz, but only after 1905 had it come to his attention! "Otherwise" he said, "I would have mentioned it in my paper!" indeed, Einstein's 1905 paper contains no mention of Μichelson's experiment or references to Lorentz's papers."<p>From <a href="https://physics.stackexchange.com/questions/89375/did-einstein-know-about-the-michelson-morley-experiment" rel="nofollow">https://physics.stackexchange.com/questions/89375/did-einste...</a><p>Correcting a professor at MIT (head of the department alas) on this erroneous belief during a grad school interview cost me admission as he insisted otherwise and wouldn't back down. Ironically, one of my college professors was interviewed on NPR a week later and confirmed what I had stated.<p>Ask me what I think of checked out, tenured academics. Go ahead...
That may be true, but Lorentz specifically cited the MM experiments and was influenced by them, and Einstein cited and was influenced by Lorentz, so he was influenced, just one level removed.<p>><a href="https://link.springer.com/chapter/10.1007/978-3-663-19510-8_1" rel="nofollow">https://link.springer.com/chapter/10.1007/978-3-663-19510-8_...</a>
No, no, you don't get it - soon Joe Sixpack will be prompting AGI "solve me {super difficult problem researchers couldn't solved for centuries}" and releasing their own research papers!
This is copium. Humans worked on it, but they didn't come close to actually solving it. Even if you do the whole "the AI looked at material in its training data" thing, modern AI can make their own math data to train on with RLVF. This new model is legitimately on a different plane of existence from modern mathematicians.
I guess this post is not worthy of the front page. It is poorly written, repetitive, and feels like it was written by a LLM. It seems more like a reactionary post about events that have already happened. There is no insightful signal whatsoever just a remix of existing rhetoric. Ironically, the blog is also called "Rough Ideas" and the homepage says that the blog may contain rough ideas. I guess Hacker News has declined in quality these days. I might get flagged for saying this.
> but that an AI system may have produced new mathematical knowledge that humanity did not have before<p>From the expose in Terence Taos blog [1], it seems the difficulty of the Navier-Stokes counter example is a delicate balancing act between having a blow-up solution and a well behaved force field. And this involves a lot of technical arguments based on already existing ideas.<p>If this is true, then the achievement of the AI is rather to correctly navigating this balancing than inventing something completely new.<p>[1] <a href="https://terrytao.wordpress.com/2026/09/07/finite-time-blowup-with-smooth-forcing-term-for-the-incompressible-porous-medium-boussinesq-and-incompressible-euler-equations/" rel="nofollow">https://terrytao.wordpress.com/2026/09/07/finite-time-blowup...</a>
For me it was a few years ago. I had seen a twitter comment referencing astrology in a spat with two black female musicians in the US. My preconception was to look up why that kind of superstition was prevalent in those circles.<p>The answer I got from chapgpt was essentially that it has very little to do with superstition and all to do with being able to use a language to talk about stuff while still not move outside cultural norms. More sort of a secret language where you can probe questions like if your boyfriend is violent, or if your friend is having an affair.<p>I think last year I saw some research on how the reading of tea leaves originated in the ottoman empire, it was remarkably similar. The point is that I learned something new that would have been extraordinarily hard to google, or even understand without putting some serious study into the subject.
The problem isn't the mental model of AI--it's the mental model of intelligence. If you think intelligence is some non-algorithmic, non-computable process then of course you won't believe that an AI can be intelligent.<p>But since Turing's time we've known that intelligence is just computation--it's not until recently that we've been able to come up with the specific algorithm.<p>Think back to Kasparov playing Deep Blue. Back then, some people (including Kasparov) believed that a computer would <i>never</i> beat a human. They felt that human creativity and ability to see the whole board would always beat brute-force computation.<p>I watched the pivotal game 5 live. There was a point where Deep Blue made a pawn move away from the main action. The commentators at the time, chess master all, almost cheered--it looked like the machine had blundered. "It's playing like a computer" they said. But one look at Kasparov told you they were wrong. Kasparov was worried. The main action resolved, but in the end, that one pawn move, 20 moves prior, left Deep Blue in a better position.<p>What modern LLMs do is apply brute-force computation to any domain expressible in language--not just a restricted chess domain. That's the algorithm.
> What modern LLMs do is apply brute-force computation to any domain expressible in language--not just a restricted chess domain. That's the algorithm.<p>Which means that companies with sufficient computational resources and money will be capable of unlocking problems thousands of times faster and more effective than any individual even when lacking the skills, just by a matter of try and error.
I'm continually perplexed by people's perception that AI would be incapable of generating new ideas or discoveries, even years ago.<p>Deterministic machines do the same stuff again and again. Add entropy and they do new original stuff. Add a checker or verifier and you can filter for new stuff that is better. At the very least here, you now have evolution.<p>There is nothing that is particularly compelling about a system that can generate new stuff that is an improvement. What's compelling if anything is the verifier, but that isn't particularly any more mysterious than LLM output already. At least not nearly as mysterious as "Meat brains have a magical ability to manifest original ideas".
It's hard to say exactly how much credit Astra gets if its training contained the research notes of Levent Alpöge and Tristan Buckmaster. Surely it's impressive to generate the result even if working from their notes but it muddies the waters on its capabilities quite a bit.<p>From <a href="https://openai.com/index/navier-stokes-solution/" rel="nofollow">https://openai.com/index/navier-stokes-solution/</a>:<p>> we cannot rule out that de-identified data derived from their usage of our products helped improve our models
This, despite the ongoing social litigation of if this is even real?<p>I believe AI is quite capable in the right circumstances, but I'm not convinced "this" is the watershed moment.
The cognitive bias in humans to believe higher intelligence is unique to humans and even supernatural is very, very strong.
It took the author until Sept. 8, 2026, to realize LLMs are not just stochastic parrots? I'm glad they did, but I'm not sure that is worthy of the front page.<p>"I remember early systems struggling with something as simple as 2+2. Then, within just a few years, we went from that to systems achieving IMO gold-medal-level performance and now, assuming this proof is correct, to a Millennium Prize problem. That completely changes how I think about the trajectory".<p>How would Sept. 8 completely change how they think about the trajectory? Seems like there has been tremendous progress at all time.
It isn't hard to conceive of things that plateau so perhaps OP thought that the 'intelligence' underlying these models would reach some mark and then level off. If instead they just keep getting smarter/better, that can really impact the highest potential use that people can imagine for them.
They still are parrots. Just properly trained with a lot of data. Doesn’t make them not useful. But that’s what they are though.
I interpret the word 'parrot' to mean incapable of creative or original thought. Solving a major maths problem that has resisted the best mathematicians for so long seems to prove otherwise (even if it were just a matter of remixing old ideas, which is not the case here).<p>What do they need to do for you to consider them non parrots, and do you consider a lot of humans as parrots?
> Solving a major maths problem that has resisted the best mathematicians for so long seems to prove otherwise (even if it were just a matter of remixing old ideas, which is not the case here).<p>I don't think we know enough about how they work to claim that. OpenAI said they had 10 THOUSANDS agents working on the problem, testing all ideas they found in the literature (including, it seems, the breakthrough of the guys who had it for the hypo viscose case).
Did it create the path to the solution, or just grab it from conversations with a researcher working on the problem?
Good question. I think we will know very soon, perhaps not for this particular math problem, but they just need to solve another one independently and we'll know for sure. My bet is that they can.
I don't know.<p>What's the tl;dr here?<p>"I'm one of the last few who needed convincing, now listen to my thoughts on what's next!"
seems to me that many advancements so far are more the product of intelligent effort than pure brilliance, i'm still hopeful that human researchers (and humans in general) will remain better at asking the right questions and making good decisions
> My belief system was shattered the day the proof was announced.<p>I can't imagine having eyes and being able to hold the wrong belief regarding AI for so long. The fact that AI can surpass humans and make novel contributions to our civilization was obvious for me at least about a year earlier.<p>You need to have pretty messianic view of humans to believe otherwise.
To me, as soon as it was obvious that training had distilled and connected abstract concepts of increasing generality, it was only a matter of time. Almost any "new" idea can be decomposed into a combination of old component concepts.<p>It was evident in GPT-3.5
> I had held a very different view of AI: that it was basically a stochastic parrot<p>imo it's been not like that for a few years now<p>(alternatively, stochastic parrots' abilities have been underestimated)
The number of people I've heard calling AI a "stochastic parrot" is concerning. You don't understand what is or isn't stochastic and you're parroting this phrase. You yourself are a stochastic parrot.
Another convert who can parrot what the detractors said/are saying and that ends with a thoughts-and-prayers socially progressive <i>umm hope this doesn’t exarcerbate hooman differences too much</i>. See you don’t need an LLM to summarize.
Are people paid to write this shite?
Yes: <a href="https://www.cnbc.com/2026/02/06/google-microsoft-pay-creators-500000-and-more-to-promote-ai.html" rel="nofollow">https://www.cnbc.com/2026/02/06/google-microsoft-pay-creator...</a>
Yeah, people are paid to promote AI and people are paid to criticize AI. Regardless of the issue money flows to pundits on both sides. Then the manufactured engagement is milked for ad profit.
AI;dr
why should i care about your mental model of anything?