English(EN) Exposing the Cost of Deep Learning Audio Development

研究发现，深度学习音频开发的能耗是训练成本的3至256倍

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-02 04:00

一篇新发表在arXiv上的研究论文强调了深度学习音频项目开发阶段所带来的显著环境成本。来自LORIA实验室的研究人员利用Grid5000计算平台的数据发现，在架构原型设计和实验过程中消耗的能量，可能比训练最终表现最佳的模型所需的能量高出3到256倍。研究结果主张在深度学习项目的整个生命周期中，更全面地报告能耗。 AI

影响凸显了AI开发中巨大且常被忽视的能耗成本，呼吁更可持续的做法。

排序理由发表在arXiv上的研究论文，详细介绍了方法和发现。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv cs.AI TIER_1 English(EN) · Constance Douwes, Paul Magron, Romain Serizel · 2026-10-02 04:00

揭示深度学习音频开发的成本

arXiv:2610.01619v1 Announce Type: cross Abstract: The environmental impact of deep learning has attracted increasing attention over the past decade. Existing studies mainly focus on the energy and carbon emissions of model training and inference, while the whole development phase…

本文如何被排名

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揭示深度学习音频开发的成本

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