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 Название: Edge AI: Convergence of Edge Computing and Artificial Intelligence
Автор: Xiaofei Wang, Yiwen Han, Victor C.M. Leung
Издательство: Springer
Год: 2020
Страниц: 156
Язык: английский
Формат: pdf (true), epub
Размер: 17.7 MB
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.
The explosive growth of data not only provides a prerequisite for the development of AI but also creates opportunities for the rise of edge computing. However, AI and edge computing, as two popular emerging technologies, are inextricably linked to each other. On the one hand, the characteristics of edge computing that can reduce latency and traffic load can provide basic guarantees for AI. On the other hand, the learning and decision-making capabilities of AI are supporting the efficient and stable operation of edge computing. The two technologies are not only mutually supporting but also merging with each other, and they are inseparable. Deep learning, as the most representative technology of AI in combination with edge computing, has made remarkable progress in many fields through cooperation with edge computing. In this background, the purpose of this monograph is to explore the relevant achievements around the relationship between edge computing and artificial intelligence.
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