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.
This content will become publicly available on March 1, 2025
Artificial intelligence (AI) has the potential for vast societal and economic gain; yet applications are developed in a largely ad hoc manner, lacking coherent, standardized, modular, and reusable infrastructures. The NSF‐funded Intelligent CyberInfrastructure with Computational Learning in the Environment AI Institute (“ICICLE”) aims to fundamentally advance
- Award ID(s):
- 2112606
- NSF-PAR ID:
- 10505606
- Publisher / Repository:
- Wiley Online Library
- Date Published:
- Journal Name:
- AI Magazine
- Volume:
- 45
- Issue:
- 1
- ISSN:
- 0738-4602
- Page Range / eLocation ID:
- 22 to 28
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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