Comment by TickleSteve

ML implies lots of training data. That gets done centrally as it would need to be done in aggregate.

You don't have low-latency training of a model and use that same model in real-time.

And in your example (admittedly small scale) 12 items of data an hour is not exactly high-data-rate, not enough to justify racks of machines.