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Data vs. Compute. The Bitter Lesson Strikes Again.
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107 Aufrufe5Likes42ChainOfThoughtAIOriginalveröffentlichung: 2026-05-21

The Bitter Lesson principle states that in machine learning, scaling data and compute power is more effective than hand-crafted features, as performance improvements follow a quadratic relationship where increasing data by 10x typically yields only about 2x improvement, meaning diminishing returns are reached relatively quickly and large-scale data providers have a significant advantage.

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