context is everything

big day tomo 🛰️

Hiring in London 🇬🇧 for my Applied AI for Startups team at @OpenAI This role is Codex focussed, combining work with top startups + ecosystem engagement Team has MLEs, ex-founder/CTOs, research engineers. And it's pretty fun. Apply below ⬇️

We’ve fixed a bug that was degrading image understanding in GPT-6 Sol and GPT-6 Luna. You should now see better results on visual tasks in the API and Codex, including computer use.

We are very proud to be founding partners of The Horowitz Andreessen Academy and I could not be more excited for the future of Entrepreneurship and Builder Education. The Academy, is led by @gaganbiyani, backed by @a16z, and @eriktorenberg and @pmarca are on the board. It is based in SF, and will serve the most promising young high school graduates to learn to build in and for the AI era. THIS is what the nextgen of the best founders have been waiting for. Applications are open theacademysf.com

Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe. GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, bringing much of its strengths into faster and more affordable models to support work at scale. We’ve also made caching and inference more efficient, and we’re passing the savings directly to you: 50% lower API prices for Sol and Luna compared with GPT‑5.6 promotional pricing.

Learnings from 1.5 years of working with frontier startups. In Agents, simple & elegant is powerful

We’re working with an independent advisory group of mathematicians to help OpenAI responsibly share advances in AI and mathematics. The group will advise on how we assess and communicate new mathematical results, uphold academic and professional standards, and build tools that support mathematical research and learning. Through this work, we want mathematicians to be at the center of shaping how AI supports mathematical understanding and how its benefits reach the wider community. openai.com/index/advisory-gr…

Last week we hosted the @OpenAI Builder Lounge in Stockholm together with @Lovable ❤️ So good to catch up with so many friends and get hands on with the founders and engineers building here. Big thanks to @JuhanaPeltomaa for organising, our team from London for coming over to support us and everyone who joined us. More to come in Stockholm! 🇸🇪 @reach_vb @AlexandrePesant @HennersBro98

openai.com/index/astra-for-l… "Astra for Law combines GPT‑6 Astra with a powerful legal search index and instructions for legal analysis and writing. Together, they amplify Astra’s capabilities across the legal practice, while giving firms and legal technology companies the freedom to build their own applications and workflows."

I agree with Dario that we need to pace the frontier. This has been a primary topic of discussions we've had at OpenAI in recent weeks. Committing to having independent evaluators with employee-like access is a great idea, and we will do the same. We'll have more to share soon.

Big overhaul on DeepSeek V4.1 using an encoder-decoder setup. Tbh they should have called it DeepSeek V5! Super cool and refreshing, though!

Now available: ChatGPT for Financial Services. This is a tailored ChatGPT Work experience that combines built-in financial data with GPT-6 Astra’s reasoning. Teams can develop research, build financial models, and create customized client materials. openai.com/index/introducing…

Hacker house leaders in Europe or the women powering the future of Nordics and Baltics @Stockholmschool @KiuasHQ Ruum Tallinn

I've spent the last 1.5 years working with the best AI startups globally. This distills my learnings on prompts. Engineers & builders, I hope it's useful 🤝

Astra is fully rolled out to Plus, Pro, Business, and Enterprise users in Codex and ChatGPT Work. Go build! And if you need inspiration, watch Astra in action, live: openai.com/gpt-tv/

The OpenAI/Navier-Stokes mathematician beef is crazy. Quick recap + my thoughts: Two mathematicians, Tristan Buckmaster and Levent Alpöge (works at Anthropic), were pursuing the Navier-Stokes Millennium Prize Problem. Their idea was to construct a perfectly smooth force that makes the fluid equations blow up in finite time. They had already proven related results and stored all their unpublished drafts in private Codex sessions. Then, boom, OpenAI drops this banger post, claiming 10,000 agents solved Navier-Stokes using what Buckmaster describes as a suspiciously similar approach. Buckmaster hears about this and thinks: “Did these mfs train on our Codex chats?” He asked whether OpenAI’s model had accessed or been trained on their private sessions. OpenAI says no specific user data was accessed. But it also says it cannot rule out de-identified data from their usage having helped improve the model. So: clear denial of direct access, no clear answer on indirect training. But it would make sense for OpenAI to train on Codex sessions: It's probably one of the main reasons they are letting people go crazy with the resets: Infinite high quality agentic training data hack This whole situation reminds me of the Claude Mythos finding a real FreeBSD vulnerability earlier this year. It was later revealed that the exact same bug had been found and patched in closely related MIT Kerberos code 19 years earlier. ...So it was in the training data. FreeBSD vulnerability solution also leveraged thousands of agents over several hours... So maybe that just increases the changes of one agent getting lucky with it's weights? Get what I'm saying? The same question now hangs over OpenAI. If the approach came from the mathematicians’ work, this is still an insane demonstration of what AI can learn and execute, but also a massive question of consent and credit. If Buckmaster and Alpöge's work isn't in the data, and 10,000 agents independently discovered the same route from scratch… This might just be AGI