Noam Brown
@polynoamial
Researching reasoning @OpenAI | Co-created Libratus/Pluribus superhuman poker AIs, CICERO Diplomacy AI, and OpenAI o3 / o1 / 🍓 reasoning models
Today, I’m excited to share with you all the fruit of our effort at @OpenAI to create AI models capable of truly general reasoning: OpenAI's new o1 model series! (aka 🍓) Let me explain 🧵 1/
It can be hard to “feel the AGI” until you see an AI master a domain you care deeply about. Everyone will have their Lee Sedol moment at a different time.
the openai IMO news hit me pretty heavy this weekend i'm still in the acute phase of the impact, i think i consider myself a professional mathematician (a characterization some actual professional mathematicians might take issue with, but my party my rules) and i don't think i…
On IMO P6 (without going into too much detail about our setup), the model "knew" it didn't have a correct solution. The model knowing when it didn't know was one of the early signs of life that made us excited about the underlying research direction!
One piece of info that seems important to me in terms of forecasting usefulness of new AI models for mathematics: did the gold-medal-winning models, which did not solve IMO problem 6, submit incorrect answers for it? 🧵
I’m giving a talk on the speed of progress on LLM capabilities in 3 hours, gotta update the slides 😭😭
1/N I’m excited to share that our latest @OpenAI experimental reasoning LLM has achieved a longstanding grand challenge in AI: gold medal-level performance on the world’s most prestigious math competition—the International Math Olympiad (IMO).
It’s truly a privilege to be able to wake up every morning, see where the latest intelligence frontier is, and help push it a little further.
Their bet allowed for formal math AI systems (like AlphaProof). In 2022, almost nobody thought an LLM could be IMO gold level by 2025.
We are seeing much faster AI progress than **Paul Christiano** and **Yudkowsky** predicted, who had gold in 2025 at 8% and 16% respectively, by methods that are more general than expected
It takes us a few months to turn the experimental research frontier into a product. But progress is so fast that a few months can mean a big difference in capabilities.
So, all the models underperform humans on the new International Mathematical Olympiad questions, and Grok-4 is especially bad on it, even with best-of-n selection? Unbelievable!
Sheryl (@sherylhsu02) was our first hire onto the multi-agent team. Within a few months of joining, she helped to make this possible. We're so lucky to have her on the team!
Watching the model solve these IMO problems and achieve gold-level performance was magical. A few thoughts 🧵