Safe closed-loop agentic dose-response experiments using MHS

During the limited Model Hardware Standard (MHS) research preview (announced by Anthropic), I led Carnegie Mellon’s work using MHS. The Model Hardware Standard is a new standard for AI agents to safely operate physical equipment in scientific research and advanced manufacturing. The specification shared in the preview is provisional. MHS is model-agnostic; we used Claude as one compatible agent in this work.

We used MHS to let an AI agent operate a liquid handler, plate reader, robotic arm, and cameras across three computers with incompatible interfaces. Serial-dilution dose-response experiments ran about three times faster than our prior workflow. This work is featured in the MHS announcement; CMU SCS also posted on LinkedIn and X.

My focus was the AI orchestration and software integration. I developed the MHS drivers for all three instruments and the layer that let an agent — we used Claude as one compatible agent in this work — run the protocol, reject a saturated curve, and rerun with a lower maximum concentration (\(R^2 > 0.98\)), within device-declared safety bounds. Integration took about eight hours, compared with the weeks of per-instrument integration that motivated the work.

Full write-up, photos, and video: Safe closed-loop agentic dose-response experiments using the Model Hardware Standard.