What is Federated Learning?

Federated Learning

Definition A distributed machine learning approach where model training happens locally on user devices, and only model weight updates — not raw data — are shared with a central server. Federated learning enables AI improvement while preserving user data privacy.

In Depth

Google pioneered federated learning for improving Gboard keyboard predictions without accessing users' keystrokes. It is especially valuable in healthcare, where patient data cannot leave hospital systems, and in mobile applications subject to privacy regulations. Challenges include communication efficiency, handling non-IID (non-identically distributed) data across devices, and defending against poisoning attacks.

Browse more terms

AI Agent AI Alignment Agentic AI Artificial General Intelligence Artificial Superintelligence Attention Mechanism AutoML Benchmark Bias (AI) Chain-of-Thought Computer Vision Deepfake Diffusion Model Edge AI Embedding Federated Learning Few-Shot Learning Fine-Tuning Function Calling GPT