Data and System Perspectives of Sustainable Artificial Intelligence

Tao Xie, David Harel, Dezhi Ran, Zhenwen Li, Maoliang Li +9 more
1/13/2025
cs.AI

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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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Cite this paper

@article{xie2025data,
  title  = {Data and System Perspectives of Sustainable Artificial Intelligence},
  author = {Tao Xie and David Harel and Dezhi Ran and Zhenwen Li and Maoliang Li and Zhi Yang and Leye Wang and Xiang Chen and Ying Zhang and Wentao Zhang and Meng Li and Chen Zhang and Linyi Li and Assaf Marron},
  year   = {2025},
  eprint = {2501.07487},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2501.07487v1}
}

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