Anthropic and Janelia launch AI platform linking lab instruments

September 24, 2026 at 09:29 PM2 min

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Anthropic and the Howard Hughes Medical Institute's Janelia Research Campus have developed a software framework called Model Hardware Standard (MHS) that lets disparate lab instruments communicate and be controlled by AI agents. Researchers at Carnegie Mellon University set up an experiment in hours using MHS, a process that typically takes months. The platform aims to eliminate bespoke coding between devices from different vendors.

Key Facts

The Model Hardware Standard (MHS) framework was developed by Anthropic and the Howard Hughes Medical Institute's Janelia Research Campus.
MHS can be integrated into any instrument with a programmable interface, allowing connected devices to communicate with each other.
Researchers at Carnegie Mellon University set up an experiment using MHS in hours, compared to months with conventional methods.
MHS connects instruments directly to AI agents, unlike the SiLA consortium's Standardization in Lab Automation system.

Platform Development

The MHS framework grew from a collaboration between US artificial-intelligence firm Anthropic and the Howard Hughes Medical Institute's Janelia Research Campus in Ashburn, Virginia. MHS includes software that acts as connective tissue to link a lab computer's operating system to the instruments, eliminating the need for bespoke solutions, according to Alek Kemeny, a technical staff member at Anthropic and leader of the MHS effort. Any device connected through MHS can communicate with any other connected device.

Lab Automation Challenge

Getting devices to talk to each other is a notoriously difficult task because instruments often come from a range of vendors and use different programming languages. Scientists and automation engineers usually write bespoke code that translates between each machine's programming language, or add extra pieces of equipment that link instruments together. MHS is not the first tool to ease communication between scientific devices; the SiLA consortium developed Standardization in Lab Automation, which provides a standard language for lab instruments. Unlike MHS, the SiLA system does not connect instruments directly to AI agents.

Research Impact

Moving from the initial idea for a research project to a functioning experiment can easily take months, says Jose Lugo-Martinez, a computational biologist at Carnegie Mellon. Using the framework, Lugo-Martinez and his Ph.D. student Sina Barazandeh set up an experiment in mere hours. Reducing that amount of time is the wow factor for us, says Lugo-Martinez.