07/10/2026
A quietly important post from Google Research last week: they have moved the federated learning behind Gboard's next-word prediction into trusted ex*****on environments, so the privacy logic can be checked by someone outside Google rather than taken on trust. Access policies go into a public transparency log, operators only ever see anonymised model weights and metrics, and there is a whitepaper alongside it. This lands closer to our work than it might look. Our lab works with faces, voices, heart rate and gaze, signals people share with us because they trust the setup. Verifiable rather than merely claimed feels like the right bar for that kind of data. Would you hand over your physiological data to a study if the privacy guarantee were independently auditable?
We announce a new Federated Learning system that provides externally verifiable privacy guarantees while shifting computation to the server to improve training speed, accuracy, and device coverage.