Over the next decade, embedded is going to experiencing the kind of innovation we haven’t seen since the late 2000s when open wireless, protocols and cryptography (and as a result, 32-bit MCUs) were introduced. Today most people think about Machine Learning as highly complex, large, and extremely memory and compute hungry — with clusters of GPUs/TPUs heating whole towns...
This is a companion discussion topic for the original entry at https://www.edgeimpulse.com/blog/embedded-ml-for-all-developers/