When big tech firms use machine learning to improve their software, the process is usually a very centralized one. Companies like Google and Apple gather information about how you use their apps; collect it in one place; and then train new algorithms using this aggregated data. The end result for users could be anything from sharper photos on your phone’s camera, to better a search function in your email app.
This method is effective, but the back-and-forth of updating apps and gathering feedback is time-consuming. And it’s not great for user privacy, as companies have to store data on how you use your apps on their servers. So, to try and address these problems, Google is experimenting with a new method of AI training it calls Federated Learning. [Read more here...]
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