403AI

  The Future of Decentralized and Federated AI: Scalability, Privacy, and Collaborative Intelligence Introduction: The Decentralized and Federated AI Landscape: Defining Key Concepts and Motivations. Decentralized Artificial Intelligence (AI) and Federated AI represent evolving paradigms in the field of machine learning, driven by the limitations of traditional centralized AI models.1 Decentralized AI fundamentally shifts AI processing and data storage from a central authority to a distributed network of devices or nodes.3 This distribution aims to enhance data privacy, security, and user control by keeping data closer to its source and reducing the risks associated with centralized data repositories.1 Federated AI, on the other hand, is a specific decentralized machine learning approach that enables multiple parties to collaboratively train a shared model without exchanging their private data.6 In federated learning, a central server typically orchestrates the training process, bu...