Can bio foundation models solve the most critical therapeutics problem, predicting which patients will respond to a therapy? Today, we share more details in a white paper on our recently reported results using @NOETIK_ai TARIO-2 to predict responders in an actual clinical trial setting with @Agenus_Bio.

check out my stack 🤗

anyone can do anything at anytime

may

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 forbes.com/sites/amyfeldman/…

Okay SF

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april

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. biomni.phylo.bio

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: reactor.inc

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: biomni.phylo.bio/ Learn more in our launch post: phylo.bio/blog/company-fundr… We are also hosting launch events - join us at South San Francisco: luma.com/n8k8qb0n Virtual: luma.com/l5ryjaij We’re also hiring! phylo.bio/careers

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.

You should go work with Jonathan. It might change your life. It changed mine.

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.

am working through responses to this! will get back to everyone within the next 48 hrs

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)

have been meaning to write an overview on this exact topic but Corin's already done it beautifully