Federated Learning represents a transformative shift in how Artificial Intelligence (AI) models are developed and deployed. Unlike traditional machine learning, where data must be centralized in one place for training, Federated Learning enables model training to occur directly across multiple distributed devices or nodes. This approach makes it possible to use the collective intelligence of diverse data sources, without compromising privacy or data ownership.