I see. My understanding from the article was that it was a novel approach to do the ML on the device but then efficiently transmit and somehow combine the resu

I see. My understanding from the article was that it was a novel approach to do the ML on the device but then efficiently transmit and somehow combine the results together into a larger model. I'm not an expert on ML (clearly). What format does the model actually take when you share it? Is it raw data (like weights for neurons or something) + the configuration of the algorithms? I understand deanonymizing data and sharing aggregated results, but I thought actually sharing that data via essentially encoding into an algorithm and then sharing that algorithm is quite different.