3 ms·

Re: Prediction at the edge, I would think that it's better if there aren't going to be any updates to the model. Or if internet access is limited. Correct me if

• the_gipsy 6y ago
  IIRC, for example phone keyboards use federated learning, where the model is further trained locally. You don't want to send every word the user types, for privacy reasons and others. Some kind of "diff" of the local model can then be sent to the cloud at some time to add up to the base model. There is still an attack vector, you can infer a bit from the "diff", but you probably can't tell exactly what the user wrote.
• tialaramex 6y ago
  Here's a nice example that like a lot of the best things is always passively present. My Pixel 2 knows what music it hears. There's a pop song playing, I kinda like it. I could pay attention to the lyrics and try to Google them or ask somebody that might know what it is... no need, I just look at my phone, "Break My Heart by Dua Lipa" it says on the lock screen. The phone will remember it heard this, so if I get home this evening and check what was that... oh, "Break My Heart by Dua Lipa". Google builds a model and sends it to phones that opted in to enable this service. It's not large, and I actually don't know how often it's updated - every day? Every week? Every month? No clue. But the actual matching happens on the device, where it's most useful and least privacy invading.