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
{"title":"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","authors":"Peizhong Ju,&nbsp;Chengzhang Li,&nbsp;Yingbin Liang,&nbsp;Ness Shroff","doi":"10.1002/aaai.12145","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":7854,"journal":{"name":"Ai Magazine","volume":"45 1","pages":"29-34"},"PeriodicalIF":2.5000,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aaai.12145","citationCount":"0","resultStr":"{\"title\":\"AI-EDGE: An NSF AI institute for future edge networks and distributed intelligence\",\"authors\":\"Peizhong Ju,&nbsp;Chengzhang Li,&nbsp;Yingbin Liang,&nbsp;Ness Shroff\",\"doi\":\"10.1002/aaai.12145\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":7854,\"journal\":{\"name\":\"Ai Magazine\",\"volume\":\"45 1\",\"pages\":\"29-34\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-02-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aaai.12145\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ai Magazine\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/aaai.12145\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ai Magazine","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aaai.12145","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

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。

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

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信