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The core argument of The Bitter Lesson is that methods relying on human knowledge, domain priors, and hand-crafted rules perform well in the short term, but in the long run are always surpassed by general methods that rely solely on compute and data.
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9/10/2026
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UnverifiedRich Sutton argued in 'The Bitter Lesson' that approaches which hard-code human knowledge into systems will ultimately always be surpassed by general methods that fully leverage computational scale.76% similarUnverified样例学习效应表明对初学者而言学习已解决的例题比自主解题更有效75% similarUnverifiedUnlike supervised learning, which relies on labeled data, reinforcement learning does not require humans to provide correct answers; instead, it allows agents to autonomously discover optimal behavioral paths through trial and error.74% similarUnverifiedIn an article titled "The Bitter Lesson" published in 2019, Sutton argued that almost all AI methods relying on human domain knowledge have ultimately been surpassed by general methods that scale with compute.73% similar
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