This is nice, and I've wanted this kind of thing repeatedly over the last 5 years! I think you often want to run little bits of CPU-based code in addition to your deep learning graph. So I think a better deployment model might be basically Lambda but with CUDA access... or something like that.

The factors that I think would make this service most valuable are low cost (think, lower than GPU's on AWS or similar, even at scale), high burst capability from cold start (1000QPS is a good target), and of course low cold start delays (< 1s, or .5s).

This led me down a rabbit hole in years past and the technical solution seems to be generally, the ability to swap models in and out of GPU ram very quickly. Possibly using NVIDIA's unified memory subsystem.