Data and System Perspectives of Sustainable Artificial Intelligence
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arXiv
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| Auteurs principaux: | , , , , , , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912186294599680 |
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| author | Xie, Tao Harel, David Ran, Dezhi Li, Zhenwen Li, Maoliang Yang, Zhi Wang, Leye Chen, Xiang Zhang, Ying Zhang, Wentao Li, Meng Zhang, Chen Li, Linyi Marron, Assaf |
| author_facet | Xie, Tao Harel, David Ran, Dezhi Li, Zhenwen Li, Maoliang Yang, Zhi Wang, Leye Chen, Xiang Zhang, Ying Zhang, Wentao Li, Meng Zhang, Chen Li, Linyi Marron, Assaf |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_07487 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Data and System Perspectives of Sustainable Artificial Intelligence Xie, Tao Harel, David Ran, Dezhi Li, Zhenwen Li, Maoliang Yang, Zhi Wang, Leye Chen, Xiang Zhang, Ying Zhang, Wentao Li, Meng Zhang, Chen Li, Linyi Marron, Assaf Artificial Intelligence 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. |
| title | Data and System Perspectives of Sustainable Artificial Intelligence |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2501.07487 |