Google unveils next-gen federated learning with TEE-based verifiable differential privacy
gaganghotra_ · x · 2026-10-02
Google Research announced a next-generation Federated Learning system with two core changes:
- Verifiable privacy: Trusted Execution Environments (TEEs) make differential privacy guarantees externally verifiable and auditable, not just algorithmic promises.
- Server-side compute: shifting part of training off-device to cut training times, improve accuracy, and expand device coverage.
The system builds on Google's four FL privacy principles since 2017: data minimization, anonymization, transparency and control, and verifiability/auditability. Prior production DP work (MF-DP-FTRL, distributed DP with Secure Aggregation) powers Gboard next-word prediction, Smart Compose, reply suggestions, and Smart Text Selection. Details in the paper "Toward provably private learning from federated data".
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