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生成性人工智能的电子废物挑战

Peng Wang1,2, Ling-Yu Zhang3, Asaf Tzachor4,5

  • 1Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, China. pwang@iue.ac.cn.

Nature computational science
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概括
此摘要是机器生成的。

生成型人工智能 (GAI) 产生了大量的电子废物 (电子废物). 实施循环经济战略可以将这些废物减少高达86%,突出显示需要主动管理.

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科学领域:

  • 环境科学 环境科学
  • 计算机科学 计算机科学
  • 材料科学 材料科学 材料科学

背景情况:

  • 生成型人工智能 (GAI) 需要大量的计算能力来进行训练和推理.
  • 电子废物 (电子废物) 的后果和GAI的管理在很大程度上仍未得到审查.
  • 大型语言模型 (LLM) 是GAI计算需求的重要贡献者.

研究的目的:

  • 量化GAI产生的电子垃圾,重点是LLMs.
  • 为GAI探索潜在的电子废物管理策略.
  • 评估循环经济原则对GAI相关电子废物的影响.

主要方法:

  • 开发一个计算动力驱动的材料流分析框架.
  • 在各种 GAI 发展场景下对电子废物流量进行量化.
  • 模拟循环经济战略对电子垃圾减少的影响.

主要成果:

  • 从2020年到2030年,GAI电子废物可能积累在120万至50万之间.
  • 地缘政治限制和快速的服务器周转率可能会加剧电子垃圾问题.
  • 循环经济战略显示,有可能将GAI电子垃圾减少16%至86%.

结论:

  • 积极的电子废物管理对于可持续的GAI发展至关重要.
  • 将循环经济原则纳入 GAI 价值链是必不可少的.
  • 处理电子垃圾至关重要,因为GAI技术继续进步.