How AI describes TensorFlow Federated

TensorFlow Federated (TFF) is an open-source framework for machine learning and other computations on decentralized data, designed to facilitate federated research and experimentation. It provides two primary interfaces: a Federated Learning API for applying federated training and evaluation to TensorFlow models, and a Federated Core API for composing novel federated algorithms. TFF supports simulating federated learning across distributed client data and can be used for federated analytics beyond learning, enabling scenarios like training on-device with locally stored data (e.g., mobile keyboards) without sending raw data to servers.