Data and System Perspectives of Sustainable Artificial Intelligence
Tao Xie
D. Harel
Dezhi Ran
Zhenwen Li
Maoliang Li
Zhi-Xin Yang
L. Wang
Xiang Chen
Y. Zhang
Wentao Zhang
Meng Li
C. Zhang
Linyi Li
Assaf Marron

Abstract
Sustainable AI is a subfield of AI for concerning developing and using AI systems in ways of aiming to reduce environmental impact and achieve sustainability. Sustainable AI is increasingly important given that training of and inference with AI models such as large langrage models are consuming a large amount of computing power. In this article, we discuss current issues, opportunities and example solutions for addressing these issues, and future challenges to tackle, from the data and system perspectives, related to data acquisition, data processing, and AI model training and inference.
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