JonLuca retweeted
The Navier-Stokes moment was always much more about the figure below than about the Navier-Stokes problem itself. The run represents a decade of mathematical progress in a week.
Can't wait to point these tools at life sciences, building our next models, and alignment!
Replying to @OpenAI
An incredible day for mathematics!
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
github.com/openai/math
JonLuca retweeted
The Decisions API is now available in public beta!
To show the power of this API, we built a demo that gives contextual agentic shortcuts to any app. It:
1. Watches your screen as you browse
2. During a pause, Decisions API suggests actions based on screen content
3. Clicking hands over control to a Decisions API-backed CUA loop
4. The task is completed ~10x faster than a traditional CUA agent
Excited to see what developers build with this API!
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
github.com/openai/math
JonLuca retweeted
Our team built the mvp of this product and in <1 week the world's largest companies were using it. No one out-ships OAI
JonLuca retweeted
I think one of the reasons people in the AI field — especially in the labs — tend to be more “AGI-pilled” than people outside is that we get to observe AI succeed at tasks that we know for a fact we didn’t explicitly train it for.
Whereas if you’re outside the labs, then in theory (stretching the imagination), every AI success so far could be downstream of some kind of costly explicit training effort by the lab insiders (which is partly but not completely true).
In other words, being a lab insider gives you a direct observation of the “magical” properties of this synthetic-brain technology. Whereas for outsiders, AI’s abilities can always plausibly seem artificial/non-magical/man-made.
This was a blast to partner on - @bea_yankelevich is doing incredible work
check out how AI helps scientists with quantum computing research
@bea_yankelevich at MIT's EQuS group used GPT-5.6 Sol with Codex to run routine measurements on quantum chips, so she could accelerate her experiment design
openai.com/index/codex-quant…
JonLuca retweeted
"We can say categorically that it is impossible for Dr. Buckmaster’s Codex prompts over the last two months to have influenced the system in any way, including training." — OpenAI spokesman in a statement
nytimes.com/2026/09/10/scien…
JonLuca retweeted
This past week at OpenAI has been the most humbling experience of my life. We all feel the weight of what’s coming.
When I joined OpenAI earlier this year, I speculated that AI might write an Annals paper in 2027—and maybe, just maybe, solve a Millennium Prize Problem in 2028. That was considered very bullish at the time. The first happened in May; the second, this September.
What a surreal time to be alive!
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics.
The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra.
The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
In every interaction I’ve had with Seb he’s been extraordinarily thoughtful and respectful. He cares deeply about mathematics and mathematicians, and has always acted with the highest integrity
I would like to clarify a few things:
1) The screenshot is my reaching out to Levent to coordinate our releases. I hope it’s clear from the message that we came in with the best possible intentions.
2) I never ever asked for Levent to be removed from authorship of his own work (as indicated by my text). I was surprised to learn during the call with Tristan that they had only solved Euler and not Navier-Stokes; after learning this we brainstormed possible paths forward. One option we discussed was that Tristan could be the lead author on a rewrite of OpenAI’s Navier-Stokes proof. It is in that context that I said “it would be simpler if Levent was not an Anthropic employee” because I felt it would be inappropriate for an Anthropic employee to author OpenAI’s work. Importantly it was admitted that internal Anthropic models had been used in their proof of Euler blowup; I therefore felt I could not consider Levent to be an independent academic. Another option I wanted to propose (but got cut short) is to offer access to our internal model so that they could try to finish their proof and bridge the gap between Euler and NS. Again I did not know how to navigate giving access to internal OpenAI IP to an Anthropic employee.
3) To reiterate it plainly: as my text clearly indicates, and as I said during our call, OpenAI's intention was to do everything possible to celebrate their mathematical achievements and the heroic efforts that they made on Euler. In the call I was immediately met with a litany of slander, including direct threats that if we were to announce Navier-Stokes he would immediately go to the press with a barrage of unfounded accusations. I refuted all these accusations but he replied “there is nothing you can do, I simply do not trust you”. I was confused why one would turn an incredible source for celebration (of their achievements!) into such bickering, which is when I said that I did not understand why one would risk their career [over unfounded accusations]. Genuinely, at that moment, I was trying to care for him and do a last ditch attempt to get a chance to give them all the credits that they deserve. I deeply apologize for this extremely poor choice of words, it is the opposite of what I was trying to convey. (I should say that I retracted them on the spot by the way.)
4) Overall, on a personal level, it was incredibly difficult to have these conversations. Levent refused to attend any of the meetings despite my repeated asking. As Sholto Douglas said, there will need to be coordination between Anthropic and OpenAI in the future; I felt I was doing a proxy negotiation with Anthropic while the Anthropic employee refused to directly participate.
JonLuca retweeted
Seeing this new internal model solve open after open math problem shortly after training commenced was the wildest thing I have ever witnessed at my time at OpenAI
Replying to @OpenAI
This model represents a step-function improvement on many benchmarks, and its training is ongoing.
Our internal model group arrived at the Navier–Stokes solution in 88 hours, using around 10,000 coordinating AI agents.
Throughout the effort, we maintained the strict safeguards—including monitoring and isolation—that we apply to all our frontier evaluations.
JonLuca retweeted
i'm sorry but if openai hears 'anthropic solved navier stokes' and races to throw a bunch of agents on it, without any information on your approach, and the agents discover the same thing (and more), still offer you dual credit in goodwill, that is totally above board
this all comes down to whether or not openai heard of tristan buckmaster's approach beforehand and seeded the model with that context. openai seems to completely deny this
there is no chance that any researcher spied on buckmaster's chats (you have to jump through multiple security and legal hoops to even get the initial credentials to access any user data, no way) and i'd be very surprised if any of buckmaster's chats were trained on at all. it's just not how modern LLM training is done
This weekend was one of the most insane weekends I’ve ever experienced. Truly feeling the AGI
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics.
The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra.
The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
JonLuca retweeted
PSA: Astra can see your remaining usage % in Codex and keep it in mind while running a /goal
so you can give it a budget in plain English like:
“keep going until i’m down to 25%, or until you've solved it”
JonLuca retweeted
We gave our AI system a spec, and in under 2 weeks, it designed, verified, and deployed a chip that beats NVIDIA.
It’s built for low-power physical AI workloads. We’re running live inference on >B+ parameter models like Llama, Qwen, and Kimi, serving at 3.4x better perf/watt than NVIDIA Jetson.
From just a specification, our AI system autonomously generated all of the RTL Design, UVM verification, formal proofs, firmware, drivers, and kernels, co-designing the model, software and silicon as one optimization loop.
Better AI can now design better chips to run AI, leading to a loop of recursive-self improvement towards our path to abundant intelligence.
Readers added context they thought people might want to know
Architect Labs did not manufacture a physical chip; the design was tested on a commercial AMD Versal FPGA board. Furthermore, the 3.4x perf/watt gain over NVIDIA Jetson is a simulation-based projection for a future 8nm ASIC, not a physical benchmark. businessinsider.com/architect-labs… architectlabs.com/architect-labs…
Someone at @1Password (@jmeller?) needs to implement a time based authorization for agents and the cli. Codex keeps asking me for ssh key access every few minutes and it’s infuriating. Sucks that you have to pick between insecure on device plaintext and being constantly annoyed
JonLuca retweeted
Today we're releasing Computer History in ChatGPT.
It lets ChatGPT learn from everything you do on your computer, so it can better understand how you work, finish tasks that you're in the middle of, and suggest skills and automations based on how you use your computer.
JonLuca retweeted
a 10 minute application for a $50,000 fellowship. no strings.
a total of $1,000,000 going out, towards making more magic in the world.
presenting the Basis Fellowship.
run by @markkhrapko ,@thewildstevenp , and spencer green























