An AI ‘matter compiler’ wants to build tiny machines from code (opens the source in a new tab)
- Atomic Machines, a start-up in Emeryville, California, trains AI on thousands of materials experiments, then feeds the resulting blueprint into a chain of 13 automated machines that build and test each part.
- Its first device is a fingertip-sized power switch for data-centre equipment: quick like a silicon breaker, without silicon’s wasted power and heat, and far smaller than a mechanical one.
- Founder Jeff Holden, who once ran Uber’s self-driving car project, sees microrobots for surgery and instant blood tests ahead. For now, engineers still assemble the parts by hand.
- 150 A
- continuous current, one switch
- 13
- machines in the chain
Why it matters If hardware can be ‘compiled’ like software, the limits shift from what silicon can do to how good the data and designs are, and AI’s power-hungry data centres get a new kind of fix.
Watch next One switch is not a factory. People still hand-assemble the parts, so whether the machines can build devices on their own, at scale and at a sensible cost, is untested. Holden’s own Theranos comparison is a reminder to wait for proof.