📄 中文摘要
人工智能在现代社会中扮演着越来越重要的角色，但其背后的能源消耗问题逐渐引起关注。大型语言模型（LLMs）的训练和运行需要大量的计算资源，进而导致显著的能源消耗和碳排放。研究表明，训练一个大型语言模型所需的电力与一个普通家庭一年的用电量相当，甚至更多。随着AI技术的不断发展，如何平衡其带来的便利与环境影响成为亟待解决的问题。通过对能源使用的量化分析，可以更好地理解AI技术的生态足迹，并推动可持续发展的实践。各界应共同努力，寻求降低AI技术环境成本的解决方案。
人工智能的环境成本：大型语言模型的能源使用测量
出处: The Environmental Cost of AI: Measuring the Energy Use of LLMs
发布: 2026年2月23日
📄 English Summary
The Environmental Cost of AI: Measuring the Energy Use of LLMs
The increasing importance of artificial intelligence in modern society raises concerns about its energy consumption. Large language models (LLMs) require substantial computational resources for training and operation, leading to significant energy use and carbon emissions. Research indicates that the energy required to train a large language model can be equivalent to the annual electricity consumption of an average household, or even more. As AI technology continues to evolve, finding a balance between its benefits and environmental impact becomes a pressing issue. Quantitative analysis of energy usage can enhance understanding of the ecological footprint of AI technologies and promote sustainable practices. Collaborative efforts are essential to seek solutions for reducing the environmental costs associated with AI.