Mark Chen

We solved Navier-Stokes! Many of my colleagues left their fields because they believed that working on AI would be the fastest way to solve their fields' grand challenges. It's surreal to see the first of those challenges fall and to watch a future we believed in become real.

Two things to distinguish: Did any human or agent look at user data as part of the Navier Stokes effort? No. Do we use user feedback and de-identified data to improve ChatGPT and Codex in a holistic way? Yes. And so does every LLM company.

GPT-6 Astra is here! This is a big moment for our research team - years of work on pretraining, reinforcement learning, and post-training have come together in our most capable and aligned model yet. It can build and test software, work across apps on your computer, and even help you take a crack at open scientific problems! Capabilities that felt like grand challenges a few years ago have become tools people can actually use. One example is Computer Use - if you’ve tried this before and felt like it was too slow or not good enough, I encourage you to give it another shot. We’ve come a long way since Operator, and it “just works” now. We’re also asking these systems to act on your behalf for more consequential work. Agents needs to stay aligned with your goals and values, think transparently, and respond to oversight even when tasks become difficult. We’ve made substantial progress on these behaviors in Astra, alongside stronger monitoring that can stop potentially unauthorized actions. That work is part of what makes this release possible. I think alignment is one of the most important research frontiers in AI, and it remains far from solved. Our ability to understand and align models has to keep pace with model capabilities. We want to give people more room to think, build, and discover with increasingly powerful tools that remain *under their control*. Huge thanks to the researchers and teams who got us here. There’s a lot more work ahead, and I’m incredibly excited about what we can make possible in the near future!

Agree with @JensenHuang: we’re entering the AGI era. The AGI era must also be the alignment era. We need to teach AI to love humanity and train AI monitors as capable as the AIs they supervise. Said best by @merettm in this thoughtful, sobering piece: https://openai.com/index/an-alien-mind

We’re excited to go big with NVIDIA and sign up for 4+ GW of capacity. This is the scale frontier training demands!

Many of our strongest researchers are choosing to focus on alignment, but we're also hiring! If you want to work at a frontier lab which takes alignment seriously and doesn't pretend it's solved, please apply.

It’s hard to overstate @michpokrass's impact on our consumer products. ChatGPT has had a rebirth under her leadership, and a lot of what we've built has been driven by her vision and conviction. Really grateful to work with her!

Another step towards intelligence too cheap to meter!

Excited to welcome Orchestra Bio and @ashokaraj_ to OpenAI as we broaden our work in AI-assisted drug discovery!

Try out Intelligent UI - every ChatGPT completion now has the potential to create a custom UI. Phenomenal for learning new things!

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!

Ok cool but can he make 24 from 3, 3, 8, 8?