resolution recovered
same 8-bit converter in the component model
Keep analog compute accurate at scale.
Maintain physical weights and column responses without moving the dense transform back onto the digital host.
recovered at half the energy
cross-converter component-model comparison
maintenance energy
at 1,000 inferences per cycle in the model
Connect measure(x) to your per-weight or per-column monitor readout.
The forward pass stays in the accelerator. No retraining enters the fast loop.
Open the quickstartCan the programmed weights or columns be monitored while inference runs?
Check compatibilityWhere it applies
Photonic matrix coresAnalog in-memory arraysNeuromorphic weight banksWavefront processorsCrossbar acceleratorsOn-device inference
What this evidence shows. And what it does not.
Controlled simulation and a published component model. No fabricated analog-AI array is claimed.