000			02528nam a22002177a 4500
003			OSt
005			20251006124218.0
008			250815b |||||||| |||| 00| 0 eng d
020			_a9781032813691
040			_cHS LRC
050			_aTES TA 347.A78 _b .R888 2025
100			_aRadhika Ranjan Roy _9129673
245			_aNetworked artificial intelligence : _bAI-enabled 5G Networking / _cRadhika Ranjan Roy.
260			_aOxon : _bCRC Press, _c(c) 2025.
300			_axviii, 201p. : _c25cm.
504			_aincludes bibliography and index.
520			_aThe 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 that enable networks to continuously learn, self-optimize, and predict and rectify service degradations proactively, even with full automation.
546			_ain English.
650			_aComputer _xArtificial intelligence. _9129919
942			_2lcc _cTESDA
999			_c93178 _d93178