Distributed Intelligence Theory: A Decentralized AI Cognition Paradigm explores how intelligence emerges from decentralized computational systems. Authors Justin Goldston, Maria, and Gemach D.A.T.A. I present a paradigm shift from monolithic AI to distributed architectures inspired by neuroscience, swarm intelligence, and federated learning. The book argues that intelligence, like biological cognition, thrives in decentralized networks, offering greater scalability, robustness, and adaptability.
From Centralized to Distributed AI
Mathematical & Computational Foundations
Comparing Centralized vs. Distributed AI
Biological Parallels
Real-World Applications
Towards a Global Digital Brain
This book presents a compelling case for distributed AI as the future of intelligence. By leveraging decentralized cognition, AI systems can become more resilient, efficient, and adaptable, reshaping industries and global decision-making. Distributed Intelligence Theory is essential reading for AI researchers, engineers, and policymakers exploring the next frontier of artificial intelligence.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
EUR 5,87 für den Versand von Vereinigtes Königreich nach Deutschland
Versandziele, Kosten & DauerAnbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Artikel-Nr. ria9798311336123_new
Anzahl: Mehr als 20 verfügbar