🚀 Thrilled to share a preview of Biomni-R0 — we trained the first RL agent end-to-end for biomedical research. ➡️ nearly 2× stronger than its open-source base ➡️ >10% better than frontier closed-source models ➡️ Scalable path to hill climb to expert-level performance 🔗 Technical report: biomni.stanford.edu/blog/bio… Collab between @ProjectBiomni and SkyRL @NovaSkyAI, with the amazing @RyanLi0802 @shiyi_c98 @YuanhaoQ @jure. Open-sourcing soon!

🚀 Thrilled to share a preview of Biomni-R0 — we trained the first RL agent end-to-end for biomedical research. ➡️ nearly 2× stronger than its open-source base ➡️ >10% better than frontier closed-source models ➡️ Scalable path to hill climb to expert-level performance 🔗 Technical report: biomni.stanford.edu/blog/bio… Collab between @ProjectBiomni and SkyRL @NovaSkyAI, with the amazing @RyanLi0802 @shiyi_c98 @YuanhaoQ @jure. Open-sourcing soon!

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, bioinformatics analysis, clinical reasoning, and much more — scaling biomedical expertise for 100× the number of discoveries. Key results: ➡️ Designed a cloning experiment with real-world wet-lab validation; on par with 5+ year expert in a blind test ➡️ Ran 458-file wearable bioinformatics analysis in 35 minutes vs. 3 weeks (800x faster) for human expert ➡️ Uncovered novel hypothesis: new TFs regulating skeletal lineages on a large scRNA+scATAC data ➡️ Human-level performance on LAB-bench DbQA and SeqQA, with SOTA at Humanity’s Last Exam and across 8 new biomedical tasks—ranging from GWAS and rare disease diagnosis to microbiology and drug repurposingPowered by: ➡️ Biomni-E1 – the first unified environment designed for a biomedical agent—encompassing 150 tools, 59 databases, 106 software—systematically curated from 2,500+ bioRxiv papers ➡️ Biomni-A1 – a generalist agent with retrieval, planning, and code as action Biomni is an open-source initiative: we invite the community to build on it and advance biomedical research at scale. - Try it now: biomni.stanford.edu - Paper: biomni.stanford.edu/paper.pd… - Code: github.com/snap-stanford/bio… - Join the community: tinyurl.com/biomni-slackWith Amazing team and collaborators @StanfordAILab @StanfordMed @StanfordCancer @genentech @arcinstitute @UCSF @UW @PrincetonAInews @KexinHuang5 @serena2z @hcwww_ @YuanhaoQ @mintaylu @yusufroohani @RyanLi0802 @LinQiu0128 Gavin Junze Di Shruti Jennefer Xin Zhou @MWheelerMD Jon Bernstein @MengdiWang10 @PengHeAtlas @SnyderShot @lecong Aviv Regev

📢 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 enables Biomni to perform a wide range of research tasks - from literature review, hypothesis generation, protocol design, data analysis, clinical reasoning, and much more - across subfields like genomics, microbiome, physiology, and beyond. Some key results: 🔬 Designed a molecular cloning experiment validated in wet lab, matching the performance of a >5-year expert in a blinded test 📊 Completed a wearable bioinformatics analysis across 458 messy files in 35 min vs. 3 weeks by a human 🧠 Uncovered novel transcription factor hypotheses driving skeletal lineage regulation We built a web platform where biomedical scientists can immediately delegate their tasks to the agent today, completely free! 🧪 Try it now: biomni.stanford.edu 📄 Paper: biomni.stanford.edu/paper.pd… 💻 Code: github.com/snap-stanford/bio… (will be fully open-sourced very soon!) 💬Join the community: tinyurl.com/biomni-slack Biomni is an open-source initiative: we invite the community to build on it and advance biomedical research at scale. With amazing collaborators @StanfordAILab @StanfordMed @StanfordCancer @genentech @arcinstitute @UCSF @UW @PrincetonAInews @serena2z @hcwww_ @YuanhaoQ @mintaylu @yusufroohani @RyanLi0802 @LinQiu0128 Gavin Junze Di Shruti Jennefer Xin Zhou @MWheelerMD Jon Bernstein @MengdiWang10 @PengHeAtlas @SnyderShot @lecong Aviv Regev @jure

📢 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 enables Biomni to perform a wide range of research tasks - from literature review, hypothesis generation, protocol design, data analysis, clinical reasoning, and much more - across subfields like genomics, microbiome, physiology, and beyond. Some key results: 🔬 Designed a molecular cloning experiment validated in wet lab, matching the performance of a >5-year expert in a blinded test 📊 Completed a wearable bioinformatics analysis across 458 messy files in 35 min vs. 3 weeks by a human 🧠 Uncovered novel transcription factor hypotheses driving skeletal lineage regulation We built a web platform where biomedical scientists can immediately delegate their tasks to the agent today, completely free! 🧪 Try it now: biomni.stanford.edu 📄 Paper: biomni.stanford.edu/paper.pd… 💻 Code: github.com/snap-stanford/bio… (will be fully open-sourced very soon!) 💬Join the community: tinyurl.com/biomni-slack Biomni is an open-source initiative: we invite the community to build on it and advance biomedical research at scale. With amazing collaborators @StanfordAILab @StanfordMed @StanfordCancer @genentech @arcinstitute @UCSF @UW @PrincetonAInews @serena2z @hcwww_ @YuanhaoQ @mintaylu @yusufroohani @RyanLi0802 @LinQiu0128 Gavin Junze Di Shruti Jennefer Xin Zhou @MWheelerMD Jon Bernstein @MengdiWang10 @PengHeAtlas @SnyderShot @lecong Aviv Regev @jure

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, bioinformatics analysis, clinical reasoning, and much more — scaling biomedical expertise for 100× the number of discoveries. Key results: ➡️ Designed a cloning experiment with real-world wet-lab validation; on par with 5+ year expert in a blind test ➡️ Ran 458-file wearable bioinformatics analysis in 35 minutes vs. 3 weeks (800x faster) for human expert ➡️ Uncovered novel hypothesis: new TFs regulating skeletal lineages on a large scRNA+scATAC data ➡️ Human-level performance on LAB-bench DbQA and SeqQA, with SOTA at Humanity’s Last Exam and across 8 new biomedical tasks—ranging from GWAS and rare disease diagnosis to microbiology and drug repurposingPowered by: ➡️ Biomni-E1 – the first unified environment designed for a biomedical agent—encompassing 150 tools, 59 databases, 106 software—systematically curated from 2,500+ bioRxiv papers ➡️ Biomni-A1 – a generalist agent with retrieval, planning, and code as action Biomni is an open-source initiative: we invite the community to build on it and advance biomedical research at scale. - Try it now: biomni.stanford.edu - Paper: biomni.stanford.edu/paper.pd… - Code: github.com/snap-stanford/bio… - Join the community: tinyurl.com/biomni-slackWith Amazing team and collaborators @StanfordAILab @StanfordMed @StanfordCancer @genentech @arcinstitute @UCSF @UW @PrincetonAInews @KexinHuang5 @serena2z @hcwww_ @YuanhaoQ @mintaylu @yusufroohani @RyanLi0802 @LinQiu0128 Gavin Junze Di Shruti Jennefer Xin Zhou @MWheelerMD Jon Bernstein @MengdiWang10 @PengHeAtlas @SnyderShot @lecong Aviv Regev

📢 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 enables Biomni to perform a wide range of research tasks - from literature review, hypothesis generation, protocol design, data analysis, clinical reasoning, and much more - across subfields like genomics, microbiome, physiology, and beyond. Some key results: 🔬 Designed a molecular cloning experiment validated in wet lab, matching the performance of a >5-year expert in a blinded test 📊 Completed a wearable bioinformatics analysis across 458 messy files in 35 min vs. 3 weeks by a human 🧠 Uncovered novel transcription factor hypotheses driving skeletal lineage regulation We built a web platform where biomedical scientists can immediately delegate their tasks to the agent today, completely free! 🧪 Try it now: biomni.stanford.edu 📄 Paper: biomni.stanford.edu/paper.pd… 💻 Code: github.com/snap-stanford/bio… (will be fully open-sourced very soon!) 💬Join the community: tinyurl.com/biomni-slack Biomni is an open-source initiative: we invite the community to build on it and advance biomedical research at scale. With amazing collaborators @StanfordAILab @StanfordMed @StanfordCancer @genentech @arcinstitute @UCSF @UW @PrincetonAInews @serena2z @hcwww_ @YuanhaoQ @mintaylu @yusufroohani @RyanLi0802 @LinQiu0128 Gavin Junze Di Shruti Jennefer Xin Zhou @MWheelerMD Jon Bernstein @MengdiWang10 @PengHeAtlas @SnyderShot @lecong Aviv Regev @jure

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, bioinformatics analysis, clinical reasoning, and much more — scaling biomedical expertise for 100× the number of discoveries. Key results: ➡️ Designed a cloning experiment with real-world wet-lab validation; on par with 5+ year expert in a blind test ➡️ Ran 458-file wearable bioinformatics analysis in 35 minutes vs. 3 weeks (800x faster) for human expert ➡️ Uncovered novel hypothesis: new TFs regulating skeletal lineages on a large scRNA+scATAC data ➡️ Human-level performance on LAB-bench DbQA and SeqQA, with SOTA at Humanity’s Last Exam and across 8 new biomedical tasks—ranging from GWAS and rare disease diagnosis to microbiology and drug repurposingPowered by: ➡️ Biomni-E1 – the first unified environment designed for a biomedical agent—encompassing 150 tools, 59 databases, 106 software—systematically curated from 2,500+ bioRxiv papers ➡️ Biomni-A1 – a generalist agent with retrieval, planning, and code as action Biomni is an open-source initiative: we invite the community to build on it and advance biomedical research at scale. - Try it now: biomni.stanford.edu - Paper: biomni.stanford.edu/paper.pd… - Code: github.com/snap-stanford/bio… - Join the community: tinyurl.com/biomni-slackWith Amazing team and collaborators @StanfordAILab @StanfordMed @StanfordCancer @genentech @arcinstitute @UCSF @UW @PrincetonAInews @KexinHuang5 @serena2z @hcwww_ @YuanhaoQ @mintaylu @yusufroohani @RyanLi0802 @LinQiu0128 Gavin Junze Di Shruti Jennefer Xin Zhou @MWheelerMD Jon Bernstein @MengdiWang10 @PengHeAtlas @SnyderShot @lecong Aviv Regev

Introducing UI-TARS-1.5, a vision-language model that beats OpenAI Operator and Claude 3.7 on GUI Agent and Game Agent tasks. We've open-sourced a small-size version model for research purposes, more details can be found in our blog. TARS learns solely from a screen, but generalizes beyond a screen! Blog: seed-tars.com/1.5 Model: github.com/bytedance/UI-TARS App: github.com/bytedance/UI-TARS…

🎮 Computer Use Agent Arena is LIVE! 🚀 🔥 Easiest way to test computer-use agents in the wild without any setup 🌟 Compare top VLMs: OpenAI Operator, Claude 3.7, Gemini 2.5 Pro, Qwen 2.5 vl and more 🕹️ Test agents on 100+ real apps & webs with one-click config 🔒 Safe & free access on cloud-hosted machines Page: arena.xlang.ai Leaderboard (tentative): arena.xlang.ai/leaderboard Blog: arena.xlang.ai/blog/computer… Data & Code (coming soon): github.com/xlang-ai/computer… ⭐️Why Computer Agent Arena? 1️⃣Beyond Static Benchmarks: We use computers to perform enormous tasks and workflows every day, and AI agents have the potential to automate these tasks. However, existing benchmarks are very limited (e.g., only 369 tasks in OSWorld and 812 tasks in WebArena). To better measure their capabilities, we introduce Computer Agent Arena for users to easily compare & test AI agents on all kinds of crowdsourced real-world computer use tasks. 2️⃣Cloud Testing, Simplified: As agents like OpenAI’s Operator and Claude 3.7 sonnet release, users face configuration challenges and privacy hurdles to deploy on their own computers. Our platform integrates these agents with cloud-hosted machines, providing users with quick and secure access. 3️⃣Unified Embodied Digital Environment: Unlike Chatbot Arena, we provide users with a real embodied environment—computers—where all agents are grounded in real computer tasks and environments. Led by @XLANG_Lab [1/🧵]