从数据与系统角度探讨如何让AI更环保
Data and System Perspectives of Sustainable Artificial Intelligence
- 从数据采集到模型推理全链路优化能耗
- 指出大模型训练与推理消耗巨大算力
- 适合关注绿色AI与可持续计算的研究者
可持续AI是关注如何以降低环境影响为目标来开发和使用AI系统的子领域。鉴于大语言模型等AI模型在训练和推理过程中消耗大量计算资源，可持续AI的重要性日益凸显。本文从数据与系统视角出发，讨论数据获取、数据处理以及AI模型训练与推理环节所面临的当前问题、机遇与示例解决方案，并展望未来需应对的挑战。
原文摘要 · Abstract (English)
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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