You can take a trained model (TPU, GPU accelerated) and replicate it to an embedded board. It would be possible to use the Cortex M4F FPU to accelerate the deep

You can take a trained model (TPU, GPU accelerated) and replicate it to an embedded board. It would be possible to use the Cortex M4F FPU to accelerate the deep learning inference functions. Using a TPU-like core on a microcontroller/SoC would be an improvement. Deep Learning inference processing is not reliant on the cloud, and once trained can work fine without any connectivity.