Federated learning represents a paradigm shift in data analysis, allowing AI and machine learning models to be trained on decentralized devices. This technique enables data to remain on the user's device, significantly reducing privacy risks associated with data transmission and storage. By minimizing central data collection, federated learning offers a promising path to privacy-preserving AI.
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