OpenAI 等用 1946 个智能体 32 分钟解读小鼠全脑 CRISPR 图谱
OpenAI showed that AI agents can handle the slowest step in modern biology, making sense of huge experiments.
OpenAI、PerturbAI 与 Scripps Research 用 1946 个 GPT-Rosalind-5.5 智能体，在 32 分钟内完成小鼠全脑 CRISPR 图谱解读，OpenAI 估计人工需数月。每个智能体只分析单个基因敲除的影响并检索文献，且未接触模型 2025 年 12 月知识截止后才发表的图谱论文，仍匹配或细化了表达数据可支持的 55 项已发表发现中的 48 项。方法核心是把一次巨型分析拆成近 2000 个单基因小任务并行执行，单个智能体处理 893 个基因时仅引用 11 篇文献，拆分后引用量为其 711 倍，盲审博士评审在 75% 的情况下更偏好拆分后的报告。
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原文给出了把一次大规模分析拆成近 2000 个智能体并行执行的量化对比，方法本身可迁移到其他超大规模数据解读。
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查看原帖GPT-Rosalind surfaced a new lead for drug discovery: could restoring cholesterol transport protect neurons from degeneration? DCTN1 is a gene linked to Perry syndrome, a rare neurodegenerative disorder. In mouse-brain data, disrupting it increased expression of genes involved in making cholesterol. GPT-Rosalind suggested a possible explanation: cholesterol…
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GPT-Rosalind surfaced a new lead for drug discovery: could restoring cholesterol transport protect neurons from degeneration? DCTN1 is a gene linked to Perry syndrome, a rare neurodegenerative disorder. In mouse-brain data, disrupting it increased expression of genes involved in making cholesterol. GPT-Rosalind suggested a possible explanation: cholesterol may not be reaching where neurons need it. That gives scientists a specific mechanism to test and, if confirmed, a direction for developing new treatments for neurodegenerative disorders. With @perturbai_tx and @scrippsresearch, a team of thousands of GPT-Rosalind agents worked in parallel, connecting gene-expression results from millions of mouse brain cells with scientific literature in just 32 minutes. We’re now expanding this collaboration to identify new drug targets. https://t.co/oHdF3ELsMj
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OpenAI showed that AI agents can handle the slowest step in modern biology, making sense of huge experiments.
By splitting a huge brain experiment among 1,946 AI agents, OpenAI got in 32 minutes what it estimates would take people months: a ranked list of leads for new brain-disease research.
So biology labs can now produce experiments far bigger than their own experts can fully interpret
OpenAI, PerturbAI and Scripps Research had 1,946 GPT-Rosalind-5.5 agents interpret a whole-brain mouse CRISPR atlas in 32 minutes.
Each agent analyzed a single knockout’s effects and searched the literature, without seeing the atlas paper, which appeared after the model’s December 2025 knowledge cutoff.
They still matched or refined 48 of the 55 published findings the expression data could support.
The main advance is the method: split 1 giant analysis into nearly 2K small ones, 1 gene per agent, and run them all at once. A single agent given 893 genes cited just 11 papers, while the split-up agents cited 711 times as many, and blinded PhD reviewers preferred their reports 75% of the time.