| 书目名称 | Edge AI | | 副标题 | Convergence of Edge | | 编辑 | Xiaofei Wang,Yiwen Han,Xu Chen | | 视频video | | | 概述 | Reviews the latest research, developments and practices concerning edge intelligence and intelligent edge.Helps readers to understand the connections between enabling technologies for edge computing a | | 图书封面 |  | | 描述 | 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 mor | | 出版日期 | Book 2020 | | 关键词 | Edge computing; Fog computing; Edge intelligence; Intelligent edge; Deep learning; Machine learning; Artif | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-15-6186-3 | | isbn_softcover | 978-981-15-6188-7 | | isbn_ebook | 978-981-15-6186-3 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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发表于 2025-3-21 18:44:19
