Google moves Gboard federated learning into verifiable TEEs

Google says its new TEE-backed federated-learning system now trains Gboard’s English and Japanese next-word models using 6,500-device cohorts, with server-side compute running in remotely attestable enclaves (the system announcement). Its 5,000-round comparison says training jobs that previously took one to two months are now chiefly limited by TEE capacity, while the allowed server workload is logged publicly in Rekor. Builders handling private user data should compare this auditable server-side model with Google’s encrypted-inference approach and include TEE side-channel limits in their threat model.