Anthropic previews AI hardware standard after early lab tests cut integration time and automate experiments The Model Hardware Standard is being tested across scientific research and advanced manufacturing, with early projects spanning drug discovery, brain imaging and quantum computing Anthropic has opened the first research preview of its Model Hardware Standard, a new specification designed to let AI agents operate physical equipment across laboratories and advanced manufacturing without building a separate integration for every device. The company says MHS can reduce hardware integration from weeks or months to hours or minutes, while giving AI agents a common way to discover equipment, understand operating limits and coordinate multiple devices. Early tests have already moved beyond simulations. Anthropic says AI agents using MHS have run a drug-discovery experiment with real-time error handling at Genentech, compressed an imaging experiment at HHMI Janelia Research Campus from weeks to a single day, and improved laser stabilization on QuEra quantum computers from 58% to 99.3%. The system is not yet open source. Anthropic is first making it available to a group of scientific research labs and manufacturers so it can expand safety evaluations and gather evidence on how AI behaves when it is given direct control over physical equipment. From bespoke integrations to a common hardware layer The problem MHS is trying to solve is straightforward: laboratory and manufacturing equipment often comes with different programming interfaces, software and data formats. Connecting devices together can therefore require specialists to build custom software for each setup. Adding an AI agent creates another layer of integration. MHS introduces a standardized driver that translates between software and the physical device. It uses basic commands such as reading a temperature or changing a setting, while also describing the characteristics and safety limits of each machine. That information can include details that