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English(EN) The inventor of the bitter lesson has a bitter lesson for LLM scaling enthusiasts

图灵奖得主:仅靠算力无法解锁人工智能,“苦涩教训”揭示局限

图灵奖得主Richard Sutton认为,仅通过增加算力来规模化大型语言模型(LLMs)不足以实现真正的人工智能。他强调需要超越当前深度学习方法的全新学习方法。前OpenAI研究员Tworek等人也持有此观点,认为对Transformer规模化的关注误导了许多科学家,而新一代初创公司正在积极探索这些替代方法。 AI

影响 建议将人工智能研究重点从扩展现有模型转移到开发根本性的新学习算法。

排序理由 一位知名研究人员关于当前人工智能规模化方法局限性的观点文章。

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图灵奖得主:仅靠算力无法解锁人工智能,“苦涩教训”揭示局限

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一位知名研究人员关于当前人工智能规模化方法局限性的观点文章。
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报道来源 [1]

  1. The Decoder TIER_1 English(EN) · Matthias Bastian ·

    “苦涩教训”的提出者给LLM规模化爱好者们上了苦涩一课

    <p><img alt="" class="attachment-full size-full wp-post-image" height="768" src="https://the-decoder.com/wp-content/uploads/2026/11/ai_scaling_bitter_lesson-2.png" style="height: auto; margin-bottom: 10px;" width="1376" /></p> <p> Turing Award winner Richard Sutton reaffirms that…