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📡 🧬 Join us for the next Foundation Models for Biology Seminar Series (#FM4Bio) session on June 4 at 9 AM PT, featuring Kexin Huang. Kexin will present KGWAS, a geometric deep learning method that uses a massive functional genomics graph to enable rare variant discovery in

Very good highlight by Sri Kosuri but I’m still saying we need to do a LOT better as a field Reliability starts with what and how it’s published. We all live in the universe of positive and exciting results. Not the much larger one of ambiguity and failure. While publishing may

Announcing Biomni — the first general-purpose biomedical AI agent. Biomni is a free web platform where biomedical scientists can immediately delegate their tasks to Biomni, starting today! Biomni automates literature reviews, hypothesis generation, protocol design,

📢 Introducing Biomni - the first general-purpose biomedical AI agent. Biomni is built on the first unified environment for biomedical agent with 150 tools, 59 databases, and 106 software packages and a generalist agent design with retrieval, planning, and code as action. This

Exciting work just out today: 🤖🧬👉 Biomni is a general-purpose AI agent for biomedical research, brought to you by Kexin Huang Jure Leskovec and team!

The Biomni biomedical AI agent I was early testing has just been released, and it’s truly very impressive for an open-source system! I’m very excited about this! Kudos to everyone involved at Stanford AI Lab and Arc Institute and others for a fantastic contribution 👏

Bravo! that's a lot of tools!

An exciting moment for scientists who could use some expert, intelligent support and for biomedicine overall

🚀 We're one step closer to creating super-intelligent AI biomedical scientists. Biomni is a general-purpose biomedical AI agent equipped with hundreds of specialized tools, software, and databases—designed to tackle the most complex questions in biology. What amazes me most?

now you can vibe code scientifically with biomni 🫡🫡🫡

Tool use offers tremendous potential for integrating LLMs into biological experiment design, perhaps even more than scaling model size. Excited to build on our earlier results with BioDiscoverAgent, now with a significantly expanded tool suite. Great collab. led by Kexin Huang!

Love this work from Kexin Huang + colleagues. An AI co-pilot in my view is a very useful, practical framing of using agents to enhance the efficiency of biomedical science. Also appreciate Kexin Huang 's grounded presentation of his work. This was clearly an immense effort

This is awesome! Great work Kexin and Jure and team. Really impressive.

Biomni is pretty good. Asked to find potential new targets for radioactive iodine resistant #thyroid cancer. These are not exactly novel, but pretty good research! #MedResearch #EndoTwitter #ThyroidCancer #ThyCa

Biomni for target discovery 👇👇

Amazing! Biomni for molecular docking ⬇️⬇️

I'm thoroughly enjoying challenging Biomni with open-ended multi-step analyses to see what type of plan it prepares, how well it can execute that plan, and how the plan is revised as various steps succeed and fail. I haven't tested it enough yet to comment on overall accuracy.

Thanks Tony for stress-testing Biomni! Very cool use case ⬇️⬇️

1/ 🚨 #FM4Bio seminar update! 🚨 Due to strong interest in Biomni, our next Foundation Models for Biology (FM4Bio) seminar with Kexin Huang will now focus on: "Biomni: A General-Purpose Biomedical AI Agent." 📅 June 4, 9:00 AM PT 📍 Save your spot: x.genbio.ai/seminar