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English(EN) The Environmental Cost of LLMs in AIED: Reporting and Practices

AIED研究人员提出追踪大型语言模型环境成本的方法

来自AIED社区的一篇新论文强调了大型语言模型(LLMs)相关的显著环境成本。研究人员发现,尽管许多AIED项目利用了LLMs,但很少有项目报告所消耗的计算资源,或将环境影响作为伦理问题进行讨论。为解决这一问题,该论文提出了一种开源方法和软件工具,用于系统地测量和报告AIED系统中LLMs的碳足迹,旨在鼓励对这些隐藏成本进行更透明的报告。 AI

影响 促进LLM开发和使用中的透明度,可能影响未来的研究和部署实践,以考虑环境可持续性。

排序理由 该集群包含一篇学术论文,提出了一种关于LLM环境影响报告的新方法论。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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AIED研究人员提出追踪大型语言模型环境成本的方法

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该集群包含一篇学术论文,提出了一种关于LLM环境影响报告的新方法论。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Sabrina C. Eimler, Lukas Erle, Daniel Flood, Aditi Haiman, Luca H\"ackert, Andr\'e Helgert, Lachlan McGinness, B\"usra Yapici ·

    AIED中大型语言模型的环境成本:报告与实践

    arXiv:2606.11215v1 Announce Type: cross Abstract: Large Language Model (LLM) usage in recent years has become increasingly widespread in the Artificial Intelligence in Education (AIED) community. While LLMs offer unique avenues for learners and educators, using LLMs comes with co…