Anthropic's new hardware standard lets AI agents control the physical world

Anthropic gave the example of a model like Claude adjusting a laser, checking the results via a separate camera, then repeating the process to automatically calibrate the whole system. MHS could also allow an AI model to focus a microscope, analyze the results, decide what part needs more observation, then automatically move the microscope to the relevant section to continue the experiment.

In a video, Anthropic also showed Claude reasoning how to get a robotic arm to pick up an aluminum can even though it had not been specifically trained on the required steps. And rather than reasoning through each step each time, Anthropic says MHS-enabled models can sequence steps across instruments by writing API scripts and adjusting them as conditions require. Anthropic introduces MHS in a promo video Anthropic says MHS also includes a standardized tagging system to describe hardware’s real-world constraints for models that may have been trained more in the virtual world.

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