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DannyB writes:

Google tool lets any AI app learn without taking all your data

A new computing tool developed by Google will let developers build AI-powered apps. The upside is it's doing so without sucking up all of your information.

Google on Wednesday released TensorFlow Federated, open-source software that incorporates federated learning, an AI training system. It works by using data that's spread out across a lot of devices, such as smartphones and tablets, to teach itself new tricks. But rather than send the data back to a central server for study, it learns on your phone or tablet itself and sends only the lesson back to the app maker.

Federated learning runs "part of the machine learning algorithm right next to where the data is on the device," Alex Ingerman, a product manager at Google Research, said in an interview. The algorithm applies what it already knows to the data on your phone, such as suggesting replies to emails, and creates a summary of what it learned in the process to send back.

TensorFlow Federated: Machine Learning on Decentralized Data

TensorFlow Federated (TFF) is an open-source framework for machine learning and other computations on decentralized data. TFF has been developed to facilitate open research and experimentation with Federated Learning (FL), an approach to machine learning where a shared global model is trained across many participating clients that keep their training data locally. For example, FL has been used to train prediction models for mobile keyboards without uploading sensitive typing data to servers.

I wonder. If the mother ship no longer gets the raw data to train, what if there is an improved learning algorithm they would like to use?

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