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English(EN) there's a hidden tax on asking AI things in your own language university of michigan measured it. same questions, three open models (qwen 3, gemma 3, llama 3.1)

AI模型在非英语语言上表现出显著的能源和准确性偏见

密歇根大学的一项研究揭示了在使用不同语言的AI模型时,存在显著的能源和准确性差异。与英语相比,使用印地语和孟加拉语等语言提示Qwen 3, Gemma 3, 和 Llama 3.1等模型需要更多的计算资源,并且响应的准确性较低。这种“隐藏的税费”不成比例地影响着数十亿不主要使用英语进行数字互动的人们。 AI

影响 凸显了非英语使用者在使用AI时可能面临的可访问性和可持续性问题,表明需要更公平的模型开发。

排序理由 研究论文,详细介绍了AI模型在不同语言上的性能发现。[lever_c_demoted from research: ic=1 ai=1.0]

在 Mastodon — fosstodon.org 阅读 →

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

AI模型在非英语语言上表现出显著的能源和准确性偏见

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研究论文,详细介绍了AI模型在不同语言上的性能发现。[lever_c_demoted from research: ic=1 ai=1.0]
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other
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报道来源 [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    用你自己的语言询问AI存在隐性税,密歇根大学进行了衡量。相同问题,三个开放模型(Qwen 3, Gemma 3, Llama 3.1)

    there's a hidden tax on asking AI things in your own language university of michigan measured it. same questions, three open models (qwen 3, gemma 3, llama 3.1): hindi used 7.9x the energy of english bengali 15.3x most western european languages: about 2x or less and the answers …