Can AI run a laboratory experiment?

Anthropic has introduced a set of technical rules called the Model Hardware Standard. Think of this as a universal language for laboratory gear. Currently, getting a microscope, a robotic arm, and a camera to work together requires engineers to write complex custom programs for every specific connection. This is slow and difficult work. The new standard allows these machines to share data and instructions through a common interface. Instead of a scientist spending weeks writing code to connect devices, an AI agent can read the standard instructions and begin operating the equipment almost immediately.

To understand why this is useful, it helps to think about how you might set up a home office. If you buy a new printer, you usually have to install a driver—a small piece of software that acts as a translator so your computer can talk to the printer. In a high-tech science lab, there are dozens of different, highly specialized machines, and they rarely speak the same language. Connecting them is like trying to plug a European appliance into an American outlet without an adapter. Anthropic’s standard acts as a universal adapter. It uses a system of tags to describe a piece of hardware to the AI. These tags explain the physical limits of the machine—such as how much weight a robotic arm can lift or the range of motion a microscope has—along with the specific actions it can perform. Because the AI now has a clear manual for how the machine works, it can reason through a task, like adjusting a laser or moving a camera, without needing a human to write a specific line of code for every step. It treats the machine as just another tool it has learned how to use.

The goal here is to automate the cycle of scientific testing. Currently, researchers spend a vast amount of time manually setting up experiments and moving equipment. If an AI can take over these repetitive tasks, a lab could theoretically run experiments around the clock, testing hypotheses much faster than humans ever could. However, this shift comes with real responsibility. When an AI controls physical gear, it can break things or create safety hazards. Anthropic is working with a group of partners, including robot manufacturers, to develop safety rules to ensure that as these agents start moving through the physical world, they follow strictly defined safety boundaries. If successful, this project aims to turn what once took a century of experimental progress into a decade of work.