Verified75% confidenceFactTime unknown
Federated learning was proposed by Google in 2016, originally to address privacy issues in model training on mobile devices.
3
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75%
Confidence
Long-term
Relevance
6/1/2026
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Related Claims
VerifiedFederated learning is a distributed machine learning paradigm proposed by Google in 2017, allowing models to be trained on local devices without uploading raw data to a central server.81% similarVerifiedFederated learning was proposed by Google in 2016, keeping data local and uploading only model gradients77% similarUnverifiedGoogle在其隐私政策中声明，免费版用户的对话数据可能被用于模型训练，与付费API版本的数据处理策略不同75% similarUnverifiedGoogle first applied federated learning to next-word prediction in the Android keyboard, and Apple applied it to personalization improvements in Siri.71% similarUnverifiedGoogle has applied Federated Learning technology to Gboard keyboard prediction.69% similar
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