Analog AI accelerators

Keep physical weights accurate.

Keep the dense transform in physics without giving the scaling advantage back to calibration.

8.4M

resident weights

depth-eight simulated stack

78.6%

top-1 agreement

versus 65.7% free-running

16,384

structured channels

75.4% agreement

2.0 MFLOP/s

control arithmetic

at a 10 Hz cycle

Integration

measure(x) is your per-weight or per-column monitor readout.

The forward pass stays in the accelerator. No retraining enters the fast loop.

Open the five-line quickstart
QUALIFY THE INTERFACE

Can the programmed weights or columns be monitored while inference runs?

Run compatibility checks
Where it applies
01Photonic matrix cores02Analog in-memory arrays03Neuromorphic weight banks04Wavefront processors05Crossbar accelerators06On-device inference
Evidence

Every number keeps its boundary.

Controlled simulation. Physical transfer remains unverified.