Networked Artificial Intelligence

5G technologies are enabling AI-based applications over the global network. This book provides a unified framework for the deep convergence of computing and communications, where the network and application/service can be jointly optimized as a single integrated system using AI. It presents a full treatment of 5G networked AI.

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The integration of fifth generation (5G) wireless technologies with distributed artificial intelligence (AI) is transforming network operations. AI is increasingly embedded in all network elements, from cloud and edge to terminal devices, enabling AI to function as a networking system. This convergence facilitates AI-based applications across the global network, with notable successes in various domains such as computer vision, natural language processing, and healthcare. Networked Artificial Intelligence: AI-Enabled 5G Networking a comprehensive framework for the deep integration of computing and communications, optimizing networks and applications as a unified system using AI.

The book covers topics ranging from networked AI fundamentals to AI-enabled 5G networks, including agent modeling, machine learning (ML) algorithms, and network protocol architectures. It discusses how network service providers can leverage AI and ML techniques to customize network baselines, reduce noise, and accurately identify issues. It also looks at AI-driven networks that enable self-correction for maximum uptime and prescriptive actions for issue resolution, as well as troubleshooting by capturing and storing data before network events.

The book presents a comprehensive approach to AI-enabled networking that offers unprecedented opportunities for efficiency, reliability, and innovation in telecommunications. It works through the approach’s five steps of Connection, Communication, Collaboration, Curation, and Community. These steps enhance network effects, empowering operators with insights for trusted automation, cost reduction, and optimal user experiences. The book also discusses AI and ML capabilities enable networks to continuously learn, self-optimize, and predict and rectify service degradations proactively, even with full automation.