AI silicon
built for discovery

XPU chips run inference and training on a fraction of the energy, built for the era of recursive self-improvement and superintelligence.

Our thesis

The substrate for all future knowledge

AI is moving from reading the internet to discovering new science, new materials, and new medicine. That is the road to superintelligence, and we build the hardware that takes it there.

Language is spent

Models have read nearly everything humanity has written, and each new round of scale buys less than the last. More text will not produce the next leap.

Experience is the new data

Models improve by acting, being scored, and learning from the result. Most of that compute goes to generating experience, and each round bakes what was learned into the model itself. That is recursive self-improvement.

Silicon sets the ceiling

Moving data costs far more energy than computing on it, and datacenters are capped by power. The machine that keeps data close sets the pace of discovery.

XPU

FPGA PrototypeComing soon

Grasshopper

Our first XPU, prototyped on an FPGA. Nearly all the energy in AI goes to moving data, so the XPU keeps it close. Dense math, sparse models, and the precisions they actually use, in one architecture.

Explore Grasshopper →
Grasshopper G0 XPU prototype board

Cluster

In development

Monolith

Connecting XPUs creates a bigger XPU. Monolith is a cluster of XPUs that behaves as one chip, running the work that dominates modern AI. Agents, experience generation, and training, all on the same silicon. More soon.

Careers

Build the future of computing

We're hiring founding engineers across the stack to bring silicon back to Silicon Valley. In person in San Francisco, with a direct hand in the research and the products.

Degrees and titles don't matter here. Send a demo of something you're proud of and we'll talk.

Contact

Get in touch

Partnerships, early access, investment, or anything else. Headquartered in San Francisco, CA, USA.