Title is no doubt crafted to get ahead of the usual online backlash, but here’s the actual announcement:

> We are announcing three new discoveries in mathematics, computer science, and physics about harmonic analysis, complexity theory, and quantum field theory.

1. Local smoothing and the Kakeya conjecture

2. The Exponential Time Hypothesis is false

3. Existence of quantum chromodynamics and completions of the Standard Model

Regarding Yang-Mills, as of a few weeks ago there has been some expectation that this (specifically completing Balaban's program for the existence part without the mass gap) could happen, though from the Anthropic side: https://nitter.meowing.monster/ElliotGlazer/status/211115394...

(Elliot Glazer seems in general to be a pretty good source to follow, however he does that...)

It is mind blowing that these long-standing conjectures and open questions are just falling by the dozen every other week. What a time to be alive.

I understand that the Exponential Time Hypothesis being false doesn't necessarily mean P=NP, but for people who are a lot more knowledgeable about complexity theory, does this update your priors significantly in the direction of P=NP?

> Our models produced a natural language proof for Yang–Mills existence on September 9th, 2026, and then subsequently produced a proof for QCD on September 18th, 2026. Given the length and complexity of the work, we postponed release until the Lean formalization completed. We finished our formalization of Yang–Mills’ existence on October 16th, 2026, which led us to develop the collaboration described here

absolutely insane

Lots of progress recently in formally verifiable domains. Really curious if this is a product of the machine learning folks behind most large language models being much more likely to have a background in math, physics, etc. Or if it is that large language models have some fundamental limitations in the more "scruffy" sciences like biology.

My guess is that in formally verifiable domains you can use RL-esque processes to get lots of good high-quality training data with reward signals (does it verify?), but the same does not apply to "scruffier" work. I would also imagine that the data volume of high-quality scientific work in "scruffy" domains is too low for the large language models to have a good manifold for "high-quality biology research". Would love to be proven wrong if anyone knows of anyone doing great scientific work with large language models in non-verifiable domains though.

ETH is false! This is one of the big long-standing hypotheses that I actually remember from university, and afaik, it was reasonable to assume it would be true; reasonable enough for a lot of papers and results to assume this for bounds or hardness proofs of common problems in parameterized complexity, anyways.

Also glad to see that one of the authors of the paper stating it is also in the loop here.

2026 is weird.

I wonder why the physicists are the only group to not want the full information released upfront? As a casual fan of physics[0] it seems like their completion of the standard model is possibly the biggest deal of all these breakthroughs, am I wrong?

[0]: PBS space time watcher

The title buries the lede quite a bit:

> The Exponential Time Hypothesis is false

Well, this is certainly different, can't say they ignored the criticism. Wonder if this is a monkey paw curls moment; if the findings continue to accelerate, most of it just isn't public now.

> In our view, these manuscripts are best understood as a form of raw research data.

Much better!

> For the computer science collaboration, the group has decided to make the natural language proof and Lean formalization public immediately, and we are publishing them directly to our GitHub repository. For the physics collaboration, the group has decided to hold off on releasing the AI-produced artifacts and instead work on writing it up themselves.

> All of these approaches involve tradeoffs. On the one hand, the collaborations empower experts to foster unpacking the results and contextualizing them in the broader academic community. On the other hand, choosing initial shepherds necessarily shapes who gets involved first and creates asymmetry of information. We welcome feedback on how to broaden participation and make this process more useful.

Very good!

I was highly critical of their approach with the earlier mathematical publications, but this is much improved.

Most importantly, they aren't releasing slop papers that would never have been published in any self-respecting journal or made it past a deep round of peer review questioning.

> We are committed to ensuring funding for researchers to independently examine, explain, and build on the results above.

> We continue to invite feedback on the best way to disclose results and engage with scientists to accelerate discovery.

Well done!

Now you need to actually LISTEN to the community and the feedback, so you aren't done yet, but this is a much better start than last time. Keep it up!

I am not sure if I side with Tao on this, or 3B1B. It's already causing quite a kerfuffle (to say the least) in the academic communities. This is the new norm now.

Science is getting out of the reach of the majority of people. In particular, EU is out of it mostly.

I wonder how much compute they are throwing at problems in ML like continual learning and sample efficiency. Also how successful they are with these. Results like in the post make me hopeful we'll see some type of so singularity soon

OpenAi needs to stop trying to please everyone. Just release the findings and give all the credit to your models/collaborators.

Honestly, I’m a bit scared but also a bit excited.

I’m currently reading Africa by John Reader which covers a lot of humanity storyline. From HN I get the humanity achievements that are happening right now.

The feeling digesting both daily is in order of magnitudes bigger than what any really exciting tv show did to me.

I honestly at this point don’t know anything about what could be possible and what couldnt.

I understand that this is really freightening, but also especially ETH being false gives even more hope that some fundamental problems could be solved in our lifetime, for example understanding universe, aging, colonization of planets and also our limits. I know I’m the minority, but these answers really interest me.

The proof appears to be a sub-exponential algorithm for #3-SAT not just 3-SAT, I think this is considered a much stronger result?

"In our view, these manuscripts are best understood as a form of raw research data."

They are staying on top of the exact formulations that spread like memes. I think this one was unfortunate. It's an analogy for a new type of thing that stops attempts to figure out what thing that is.

That said, uh, let's go? Let's see if OpenAI earns some goodwill here. It probably can't go worse than the last math drop!

In my opinion its okay for them to work on science and math problems and release the results.

I wonder how many prompts for proof approaches they stole for these. Nothing on how many tokens were burned.

Proud to funnel money through the Simons Foundation, which is an AI booster itself and completely aligned with OpenAI.

They make it very hard to enjoy a single result with the business and the politics being so dirty.

I'm going to be the cynical one and offer this translation: "Our results are too important to wait for the pesky peer review, so we are dumping a whole ton of money in a fund and giving some elites a breathless first look so our buzz keeps getting jacked up."

The reality that Science is a grind and there are thousands of new results every year discovered by regular humans who use a regular human process to cross-check and review.

Treating every result from the AI like a gift from god is getting tiring.

Terrible title. I was hoping to see more interesting comments on the story, haha!

In the Star Trek Voyager capstone episodes titled "Scorpion" parts 1 & 2, Chakotay explains to Janeway the behavior of the Borg through the parable of the fox and the scorpion making a transactional deal to cross the river together. After reaching the shore, the scorpion stings the fox, and the dying fox asks why. The scorpion replies, "Because it is in my nature."

(Upside of the story is Captain Janeway's trusted crew works together to formulate a trick up their sleeve precisely in case of predicted contingency...)

"Working with PR to make us look less like cheating mind leeches".

Working with academic communities lol.

I looked over the announcement for any substantial contribution, and found they're donating $5 million to a research foundation.

$5 million might sustain 5-10 PhD students for 5 years.

Maybe it's just me but I think they should contribute more in exchange for forcing the scientific community into paying for tokens to generate slop and then pouring their time into verifying or falsifying the slop.