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Category: Emerging Concepts
Category: Emerging Concepts
Federated learning trains AI models across multiple devices or servers without centralizing the data, preserving privacy while enabling collaborative learning.
Instead of sending data to a central server, federated learning sends the model to where data lives. Devices train locally and share only model updates, not raw data.
These updates combine to improve the global model without exposing individual information.
Federated learning enables AI training on sensitive data like medical records or personal phone usage without privacy violations. It makes AI development possible in regulated industries.
Companies like Google use it for features like predictive text while keeping messages private.
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