Encryption, Federated Learning, Computation, Pets, Privacy.
multiple decentralized devices without transferring the raw data to a central server. Each device uses its own local data to train the model, and only aggregate updates are sent to the central server. Due to the raw data being on the devices and never being shared, this helps protect data privacy.