TensorFlow Federated (TFF) is an open-source framework for machine learning and other computations on decentralized data. 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.
In other words, a model that say runs on an edge device at a farm can be trained using data from many farms, however crucially, each farm does not release their own data, which may be commercially sensitive.
In addition, the programming abstractions we offer are quite generic, and could be used, e.g., to implement analytics and other custom types of computations over distributed data.