Edge Intelligence: the Confluence of Edge Computing and Artificial Intelligence
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Along with the deepening development in communication technologies and the surge of mobile devices, a brand-new computation paradigm, Edge Computing, is surging in popularity. Meanwhile, Artificial Intelligence (AI) applications are thriving with the breakthroughs in deep learning and the upgrade of hardware architectures. Billions of bytes of data, generated at the network edge, put great demands on data processing and structural optimization. Therefore, there exists a strong demand to integrate Edge Computing and AI, which gives birth to Edge Intelligence. In this article, we divide Edge Intelligence into AI for edge (Intelligence-enabled Edge Computing) and AI on edge (Artificial Intelligence on Edge). The former focuses on providing a more optimal solution to the key concerns in Edge Computing with the help of popular and effective AI technologies while the latter studies how to carry out the entire process of building AI models, i.e., model training and inference, on edge. This article focuses on giving insights into this new inter-disciplinary field from a broader vision and perspective. It discusses the core concepts and the research road-map, which should provide the necessary background for potential future research programs in Edge Intelligence.
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