Anthropic 推出了其新的模型硬件标准 (MHS) 的研究预览版，旨在为 AI 代理安全操作物理设备创建统一的接口。该计划与 HHMI Science 合作开发，旨在减少将 AI 与硬件集成的时间和复杂性，将集成时间从数周缩短到数小时或数分钟。早期测试表明，MHS 使 AI 代理能够执行复杂任务，例如运行药物发现实验、压缩成像实验以及改进量子计算机上的激光稳定性。 AI
影响 该标准有可能显著加速 AI 代理与物理系统在研究和制造领域的集成，从而实现更复杂的自主操作。
排序理由 主要 AI 实验室推出新行业标准的产品。
AI 生成摘要 · Google Gemini · 来自 7 个来源。 我们如何撰写摘要 →
完整方法见我们的编辑标准。
Watch the story of how the Model Hardware Standard began as part of our collaboration with @hhmi_science https://t.co/TaeDJGk5am
We’re inviting stakeholders across science, robotics, electronics, and manufacturing to join the research preview and help shape the standard. We look forward to moving MHS forward with our industry partners and, soon, the open-source community. https://t.co/XQ2y9EW7Af
MHS currently best covers lab and manufacturing equipment. Many developers are already using Claude Code to operate hardware like boards and cameras; our research preview will help us extend MHS to these devices, so they can all work under one interface.
There’s more to learn before we open source MHS. LLMs still lack physical intuition, having learned about the physical world from text and images. The research preview will let us build more safety evaluations and strengthen protections for using AI in the physical world.
In early testing, AI agents used MHS to: Run a drug-discovery experiment with real-time error handling at Genentech Compress an imaging experiment from weeks to a day at HHMI Janelia Research Campus Improve laser stabilization on QuEra's quantum computers from 58% to 99.3%
Connecting AI to hardware requires days or weeks of bespoke integration, with no standard way for agents to operate equipment safely. MHS cuts integration to hours or minutes, provides an interface that makes devices discoverable, and enables agents to operate them safely.
Today, we're kicking off the first phase of the research preview for Model Hardware Standard (MHS): a new standard for AI agents to safely operate physical equipment in scientific research and advanced manufacturing. Read more: https://t.co/XQ2y9EW7Af https://t.co/kgyCvZ6iYc