Periodic Labs

appreciate @pronounced_kyle's framing of "read" "write" access between digital and physical worlds. One of the fundamental challenges for automating manufacturing is to solve for the digital-to-physical "write" access and…

Ekin Dogus Cubuk of @periodiclabs on why AI has to learn from the physical world, and building their own lab to close that loop: "One of the more fundamental ways of making things around us is powder synthesis... You can actually, using…

AI models are getting close to designing hardware better than humans, and that shifts where the hard problems are: - Better simulation, so physical builds become confirmation instead of experiments - Demand shifts toward parts, machining…

"It took me three months to design it, but it's nine months until I can actually start to use it." Former Intel CEO Pat Gelsinger on the manufacturing bottleneck between designing hardware with AI and actually getting it built: "Let's say…

For AI to become a superhuman hardware engineer, it has to learn from the physical world, and real-world data is hard to get: - It's non-uniform and constantly changing - It's sparse: you can't measure everything all the time - It's…

AI is on track to become a superhuman hardware designer, but design is only the beginning. The interface between bits and atoms is lossy, and turning designs into real hardware gets harder at every level: 1. Sourcing off-the-shelf parts…