It’s official: local AI inference at the edge uses less power than the cloud

It is widely assumed that running AI/ML inference on-device in an edge microcontroller uses less power than transferring the raw data to the cloud, and then performing the inference on a cloud server. Intuitively, it seems obvious: an edge device such as an Ensemble or Balletto MCU has a much smaller power footprint than even a purpose-built AI inference server in the cloud. And when inference is performed locally, the system saves the power which would be used by an RF circuit to transmit data to the cloud.