AI-EDGE:面向未来边缘网络和分布式智能的国家科学基金会人工智能研究所

IF 2.5 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Ai Magazine Pub Date : 2024-02-10 DOI:10.1002/aaai.12145
Peizhong Ju, Chengzhang Li, Yingbin Liang, Ness Shroff
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摘要

本文重点介绍了美国国家科学基金会未来边缘网络与分布式智能人工智能研究所(AI-EDGE)的总体工作,该研究所旨在为发展下一代边缘网络(6G 及以后)和人工智能(AI)领域的技术领先地位创造一个研究、教育、知识转让和劳动力发展环境。AI-EDGE 的研究目标包括两个方面:"网络的人工智能 "和 "人工智能的网络"。前者开发新的基础人工智能技术,以革新下一代边缘网络的技术;后者开发先进的网络技术,以增强边缘设备的分布式和互联人工智能能力。这些研究调查跨越八个共生的重点领域,共同应对实现这些目标的主要挑战。这种协同方法确保了研究的良性循环,使一个领域的进展将加速另一个领域的进展,从而为新一代网络铺平道路,这些网络不仅要智能,还要高效、安全、自愈,并能解决大规模分布式人工智能挑战。本文还概述了该研究所在教育和劳动力发展以及扩大参与和加强合作方面所做的努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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AI-EDGE: An NSF AI institute for future edge networks and distributed intelligence

This paper highlights the overall endeavors of the NSF AI Institute for Future Edge Networks and Distributed Intelligence (AI-EDGE) to create a research, education, knowledge transfer, and workforce development environment for developing technological leadership in next-generation edge networks (6G and beyond) and artificial intelligence (AI). The research objectives of AI-EDGE are twofold: “AI for Networks” and “Networks for AI.” The former develops new foundational AI techniques to revolutionize technologies for next-generation edge networks, while the latter develops advanced networking techniques to enhance distributed and interconnected AI capabilities at edge devices. These research investigations are conducted across eight symbiotic thrust areas that work together to address the main challenges towards those goals. Such a synergistic approach ensures a virtuous research cycle so that advances in one area will accelerate advances in the other, thereby paving the way for a new generation of networks that are not only intelligent but also efficient, secure, self-healing, and capable of solving large-scale distributed AI challenges. This paper also outlines the institute's endeavors in education and workforce development, as well as broadening participation and enforcing collaboration.

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来源期刊
Ai Magazine
Ai Magazine 工程技术-计算机:人工智能
CiteScore
3.90
自引率
11.10%
发文量
61
审稿时长
>12 weeks
期刊介绍: AI Magazine publishes original articles that are reasonably self-contained and aimed at a broad spectrum of the AI community. Technical content should be kept to a minimum. In general, the magazine does not publish articles that have been published elsewhere in whole or in part. The magazine welcomes the contribution of articles on the theory and practice of AI as well as general survey articles, tutorial articles on timely topics, conference or symposia or workshop reports, and timely columns on topics of interest to AI scientists.
期刊最新文献
Issue Information AI fairness in practice: Paradigm, challenges, and prospects Toward the confident deployment of real-world reinforcement learning agents Towards robust visual understanding: A paradigm shift in computer vision from recognition to reasoning Efficient and robust sequential decision making algorithms
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