Aptos: Creating ML models that fit your edge device like a glove
Shipping edge AI shouldn’t feel like a marathon through model zoos, missing ops, and latency ceilings. We lay out a practical path to get from your data and constraints to a hardware-ready model—measured on real boards—without the endless back-and-forth between data science and firmware teams. If you’ve wrestled with quantization loss, unsupported kernels, or picking the “right” NPU, this walkthrough will feel like oxygen.
We start by naming the pain: quick demos that collapse under real device limits, foundation models that fail after export, and feedback loops that burn months. From there…
The skinny
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