Adaptive machine learning in federated cloud environments: Advancing data-centric AI

This article examines the integration of adaptive machine learning (ML) within federated cloud environments, with a particular focus on its potential to advance data-centric AI. The study reviews the current landscape of federated learning, analyses the challenges and opportunities it presents, and evaluates adaptive ML techniques designed to enhance data privacy and model performance. Combining theoretical analysis with practical case studies, the paper offers valuable insights into the implementation of adaptive ML in federated cloud settings. The findings emphasise the significance of adaptive strategies in improving the efficiency, scalability, and security of AI models in distributed environments.