Google deploys attestable federated learning for Gboard
Google Research described a production federated-learning system that moves encrypted device examples into server-side trusted execution environments, binds decryption to published access policies and reproducible code, and releases only differentially private model weights and metrics. Google says Gboard has used it for English and Japanese next-word prediction.
Why it matters: The design makes allowed server workloads externally inspectable instead of asking users and auditors to trust the operator's implementation. It also shifts the compute bottleneck from intermittently available phones to parallel server TEEs, widening the…