TY - BOOK ID - 65497668 TI - Edge AI : Convergence of Edge Computing and Artificial Intelligence AU - Wang, Xiaofei. AU - Han, Yiwen. AU - Leung, Victor C. M. AU - Niyato, Dusit. AU - Yan, Xueqiang. AU - Chen, Xu PY - 2020 SN - 9811561869 9811561850 PB - Springer Singapore DB - UniCat KW - Artificial intelligence. KW - Computer communication systems. KW - Computer organization. KW - Artificial Intelligence. KW - Computer Communication Networks. KW - Computer Systems Organization and Communication Networks. KW - Organization, Computer KW - Electronic digital computers KW - Communication systems, Computer KW - Computer communication systems KW - Data networks, Computer KW - ECNs (Electronic communication networks) KW - Electronic communication networks KW - Networks, Computer KW - Teleprocessing networks KW - Data transmission systems KW - Digital communications KW - Electronic systems KW - Information networks KW - Telecommunication KW - Cyberinfrastructure KW - Electronic data processing KW - Network computers KW - AI (Artificial intelligence) KW - Artificial thinking KW - Electronic brains KW - Intellectronics KW - Intelligence, Artificial KW - Intelligent machines KW - Machine intelligence KW - Thinking, Artificial KW - Bionics KW - Cognitive science KW - Digital computer simulation KW - Logic machines KW - Machine theory KW - Self-organizing systems KW - Simulation methods KW - Fifth generation computers KW - Neural computers KW - Distributed processing UR - https://www.unicat.be/uniCat?func=search&query=sysid:65497668 AB - As an important enabler for changing people’s lives, advances in artificial intelligence (AI)-based applications and services are on the rise, despite being hindered by efficiency and latency issues. By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial. To do so, it introduces and discusses: 1) edge intelligence and intelligent edge; and 2) their implementation methods and enabling technologies, namely AI training and inference in the customized edge computing framework. Gathering essential information previously scattered across the communication, networking, and AI areas, the book can help readers to understand the connections between key enabling technologies, e.g. a) AI applications in edge; b) AI inference in edge; c) AI training for edge; d) edge computing for AI; and e) using AI to optimize edge. After identifying these five aspects, which are essential for the fusion of edge computing and AI, it discusses current challenges and outlines future trends in achieving more pervasive and fine-grained intelligence with the aid of edge computing. ER -