律动BlockBeats|8月 28, 2026 08:48
**[Anthropic Connects AI to Real-World Machines: Reducing Weeks of Hardware Integration to 8 Hours]**
Beating AI News Flash: Anthropic has launched the Model Hardware Standard (MHS) as a research preview, enabling AI agents to directly operate real-world machines. Microscopes, liquid processors, robotic arms, and even laser systems in quantum computers can now be integrated through a unified interface. Previously, connecting devices from different manufacturers typically required custom interface development, often taking weeks or even months. Anthropic claims that MHS can reduce this process to mere hours or even minutes.
MHS can be understood as a unified "hardware interface" layer. Once devices are connected to the MHS driver, they communicate with the agent in a standardized format, detailing their capabilities, current status, and safety restrictions that cannot be breached. The agent then operates the devices via MCP, command lines, or APIs without needing to write a separate connection program for each machine. MHS is not tied exclusively to Claude; other models and agents can also integrate with it.
Real-world testing has already been conducted. Carnegie Mellon University successfully connected an experimental automation system—typically requiring weeks to set up—in approximately 8 hours, tripling the speed of experiments. Quantum computing company QuEra used Claude to automatically optimize laser recovery programs, achieving a success rate of 99.3% in 695 out of 700 blind tests. AWS, Hugging Face, Raspberry Pi, Universal Robots, and others are also integrating with MHS.
However, MHS is not yet an open standard and is currently available only to select research institutions and manufacturers through application. Anthropic plans to conduct further safety testing before open-sourcing it. At this stage, Claude's understanding of the physical world remains limited. During Genentech's testing, Claude was unable to independently determine that liquid foaming was a physical malfunction, requiring researchers to clarify that it was not a software issue. [Original Article Link]
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