Off-device and on-device are alternatives to do deep learning inference on pi, both with pros and cons. For an example, with on-device inference, you will need to run a smaller architecture to get decent FPS and will also be dependent on hardware. Using cloud API removes those restrictions but there will be some latency in the web request however you can use much more accurate model and will be independent of pi hardware. Just trying to paint a complete picture. Any suggestions for blog post are welcome.