Own Intelligence
The chip we're building doesn't run an AI model. It is one. Trained weights are embedded physically into the silicon — permanent, parallel, present. There's nothing to load from memory because the model isn't stored as data. It's the structure itself.
Modern inference doesn't need full-precision arithmetic. Compact representations preserve accuracy with dramatically less compute, opening the door to architectures where weights and compute occupy the same physical space. The result: orders of magnitude lower energy per inference than conventional hardware.[1]
[1] Entrit Systems, forthcoming. Corroborating work: PrismML (white paper and model release, 2026, huggingface.co/prism-ml); BitNet b1.58, Microsoft Research, 2024.
No latency.
No network.
No dependency.
Metal Intelligence.
Entrit Systems Inc.
Contact
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