You probably don’t even need permission from anyone or anything to do the thing you’ve been thinking of endlessly. You could literally just start right now
I’m delighted to announce @chaidiscovery's collaboration with @pfizer. Their scientists will deploy our AI platform to accelerate drug discovery, including early access to our latest frontier model Chai-3.
You can learn more about this partnership and our momentum in @amyfeldman's feature in @Forbes out today
https://t.co/VBoynDgPCz
We’re bringing new capabilities to GPT-Rosalind, a model series purpose-built for life sciences research at enterprise scale.
It brings GPT-5.5’s agentic coding and tool use together with stronger intelligence for drug discovery, analysis, design, and experimental workflows.
https://t.co/SrAJ3Mt7ka
Biomni Lab is now GA!
During preview, researchers accomplished 20 months of work in one, collectively saving >5M hours of research.
Today we're launching a Pro tier alongside free access: higher limits, priority HPC, and more concurrency.
https://t.co/4JZfaDSJhV
Big update: I’m starting a new company.
6 months ago, @_bschmidtchen and I made a bet. What if entire worlds could be generated on the fly, pixel by pixel?
World models are the next platform shift, and we saw it coming.
Since then, we’ve:
- secured major contracts across media and physical AI industries
- assembled a team of 10+ from Apple, Meta, Google, Adobe & Microsoft
- raised from top-tier investors
More details soon. We’re scaling fast, and hiring now.
Come build with us: https://t.co/MHTPVxS5et
Today we’re launching Phylo, a research lab studying agentic biology, backed by a $13.5M seed round co-led by @a16z and @MenloVentures / Anthology Fund @AnthropicAI.
We’re also introducing a research preview of Biomni Lab, the first Integrated Biology Environment (IBE), where we’re imagining a new way biologists work.
Biomni Lab uses agents to orchestrate hundreds of biological databases, software tools, molecular AI models, expert workflows, and even external research services in one workspace, supporting research end-to-end from question to experiment to result.
Agents handle the mechanics, while you define the question, then review, steer, and decide. Scientists end up spending more time on science: asking questions, understanding mechanisms, and eliminating diseases.
Phylo (@phylo_bio) is a spin-out of @ProjectBiomni, where we will maintain the open-source community and push open-science research. I’m grateful to continue building with my co-founders @YuanhaoQ@jure@lecong and the dream founding team @serena2z@TianweiShe @huangzixin20151 @gm2123@margaretwhua@malayhgandhi.
We’re also fortunate to be advised by leading scientists @zhangf, Carolyn Bertozzi, and @fabian_theis, and supported by an amazing group of investors including @JorgeCondeBio@zakdoric Matt Kraning @ZettaVentures@dreidco@conviction@saranormous@svangel@valkyrie_vc and others.
Biomni Lab is available for free today: https://t.co/zYcXEjvIbb
Learn more in our launch post: https://t.co/O09cnwYeNg
We are also hosting launch events - join us at
South San Francisco: https://t.co/4Xm9DFf4cY
Virtual: https://t.co/Wf7ksnWkRy
We’re also hiring! https://t.co/PABaLLwmRx
2026 will be the year of AI-for-science (and my team at @huggingface is hiring for that!)
We laid up the pins in 2025, and now we’re gonna knock them down
With a new year comes a new Editor-in-Chief! Please give a warm welcome to Laurent Charlin (@lcharlin, @HEC_Montreal and @Mila_Quebec)!
He rounds out the team with Gautam Kamath (@thegautamkamath), Naila Murray (@NailaMurray) and Nihar Shah to help lead TMLR through 2026.
I'm hiring interns for next summer at @databricks! Specifically on (1) empirical RL at scale on non-verifiable tasks and (2) enabling real people specify the behaviors they want out of AI (e.g., through evals) on highly complex tasks. 🧵
Exciting update: I’ve joined @AnthropicAI as a researcher.
The potential to fight disease is core to why I believe we should keep improving AI (for now). Grateful to work on this problem at a company whose philosophy on AI for good resonates deeply with me.
Onwards!
I've got something new for everyone. My first substack article! Not the one I planned to do first, but a fun one!
I have made a handy calculator base on the DeepSeek v1 coefficients for finding optimal LR and batch sizes for dense LLMs.
I am specifically looking for a talented early career researcher (or engineer looking to break into research)!
- Fast ramp-up to work on frontier capability evaluation at pre-training & post-training stages
- Abundant technical mentorship and exposure to major model labs
- In-person out of a very special space in Dogpatch
- Work towards the only research direction that matters (bonus points if you have a good guess for what this is)