We already did this for Object/Face recognition, it works but it's not the way to go. It's the way to go only if you don't have enough compute power (and data, I suspect) for a E2E network
No, it's what you do if your model architecture is capped out on its ability to profit from further training. Hand-wrapping a bunch of sub-models stands in for models that can learn that kind of substructure directly.
