Episode Details

Daniel wants to upscale a blurry photo on a train, no cloud involved. The hardware is ready — Snapdragon 8 Gen 4 and Dimensity 9400 both pack over 40 TOPS of NPU performance. But the software path is still up for grabs. Do you quantize a general model like Real-ESRGAN to run anywhere, or build something bespoke for each chip? We break down the tradeoffs: sub-10ms specialized hardware versus 200ms general inference, three-megabyte Apple Core ML models versus sixty-five-megabyte quantized networks, and what it all means for the future of edge AI.