AI at the Edge: The Privacy Revolution of Federated Learning

As AI models demand increasingly massive datasets, moving raw data to centralized servers poses severe bandwidth and privacy risks. Federated Learning shifts this paradigm by bringing the training algorithm directly to edge devices, ensuring sensitive data never leaves the user's hands. This decentralized approach establishes a new standard for privacy-first, highly scalable machine learning architectures.