Building the brain.

The first silicon that operates the way neural tissue does. Not a model of the brain. The actual computational principles, encoded in hardware.

A new kind of computer

Every processor on the market descends from the same seventy-year-old idea. We started over.

Architecture

Circuits that spike

Conventional chips cycle through instructions whether or not there is work to do. Ours fire only when a signal crosses threshold — the same logic neurons have used for half a billion years.

Computation

Zero waste

Energy is consumed only when information changes. Silence costs nothing. This is not a power-saving feature — it is how the architecture works.

Learning

It adapts on its own

Weights adjust locally, in real time, without a training loop. No gradients. No server. The chip rewires itself the way synapses do — through use.

Efficiency

Brain-scale. Brain-power.

The human brain runs a hundred trillion synapses on twenty watts. Our architecture reaches that envelope. Not through optimization — through physics.

20 Wsustained, full-network
vs. 500W+ GPU inference
100T
Synapses modeled at full scale
20 W
Total power at cortical density
<1 ms
Signal-to-response latency

This changes what computers can be.

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SEM — microfluidic silicon chip
IC die photograph — LF444
SEM — crystalline nanostructures
STM — single molecule
Chladni vibrational pattern
Abstract filament structure