Anthropic's Model Hardware Standard aims to let AI agents control lab machines

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Anthropic wants AI agents to control programmable machines through common software rules

Model Hardware Standard (MHS) can connect microscopes, robotic arms, and liquid handling equipment

MHS allows different laboratory devices to communicate through standardized software drivers

Anthropic opened a preview of its Model Hardware Standard (MHS), designed to let AI agents control programmable machines through shared rules.

The proposed system is intended for laboratories, factories, and workplaces where different instruments must work together without custom software links.

MHS uses software drivers that translate between computer systems and individual machines, allowing equipment with different interfaces to communicate consistently.

A common system for physical machines

Its drivers rely on basic commands for reading measurements or changing settings, giving agents a method for controlling connected equipment.

The system records machine details that might otherwise remain inside manuals or depend on knowledge held by experienced laboratory staff.

Users can enter such information through natural language, after which MHS creates reference material describing capabilities, adjustments and safety restrictions.

Agents can then discover compatible equipment across networks without requiring separate software bridges for every machine they need to operate.

The standard supports microscopes, liquid handlers, robotic arms and other equipment that offers some form of programmable interface for agents.

The company claims integration that once required weeks or months could instead take hours or minutes when equipment supports MHS.

According to Anthropic , Claude was tested with physical experiments, including laser alignment supported by camera-based observation during early physical trials.

The model successfully adjusted the laser, checked the image, and repeated the process while assessing each change carefully.

The design also lets agents combine commands from several devices, creating automated sequences for work that might otherwise require coordination.

Physical limits remain a concern

Anthropic said Claude interacts with experiments and hardware in an “exploratory manner, much as a scientist would,” during physical testing.

That model can then coordinate several instruments through one interface, rather than requiring separate control software for every connected device.

The company has shared MHS with manufacturers and research groups working across biotechnology, robotics and quantum computing fields.

Anthropic intends the preview to help establish safety checks before the standard becomes available widely to developers and equipment makers.

Amazon Web Services, Automata, Danaher, Doosan Robotics, MBF Bioscience, QIAGEN, Tecan and Universal Robots are among the early participants now.

Anthropic acknowledges that AI agents still require expert supervision because language models have clear limits when reasoning about physical equipment.

MHS cannot currently support equipment lacking a programmable interface, leaving some laboratory and industrial machines outside its current technical scope.

Anthropic says it plans to work with manufacturers to add drivers while expanding compatibility with more devices and robotics platforms.

The preview will also support new safety tests and practical rules for deploying AI agents around physical equipment.

The company says its eventual open-source release will include findings from these tests alongside detailed guidance for safer implementation.

The project therefore remains experimental, with practical limits still depending heavily on hardware design, software access and human oversight.