On: Edge Computing at Chick-fil-A

[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.

[coffeesn0b → TickleSteve]

You’re correct, training is centralized but the devices that use it to function are operated at the edge.

[TickleSteve → coffeesn0b]

Of course, thats how ML works, central training of a model with use of that model at the edges.

So how often do you distribute a new model for controlling fries?