The Promise of Federated Learning: Collaborative AI without Centralized Data
Federated learning is revolutionizing artificial intelligence by allowing models to be trained across decentralized devices without exchanging raw data. This article explores how federated learning ensures privacy, reduces data silos, and enables collaborative machine learning. With applications in healthcare, finance, and personalized services, federated learning represents a groundbreaking approach to harnessing collective intelligence while preserving individual privacy. As this technology matures, it holds the potential to reshape the landscape of AI development and data governance.