Unverified50% confidenceFactExact time
规模定律（Scaling Laws）指模型性能随参数量、训练数据量和计算量的增加呈幂律提升，但某些能力呈现相变般的非线性跳跃
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8/28/2026
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Unverified单纯扩大参数规模带来的性能提升呈现边际递减趋势，被称为Scaling Law的天花板效应77% similarUnverifiedOpenAI、DeepMind等机构的研究表明模型性能随参数量、数据量和计算量的增加呈幂律提升（Scaling Law）71% similarUnverified在收敛型任务上，模型达到一定规模后存在明显的性能饱和现象，即scaling law的收益递减区间70% similarUnverifiedOn convergent tasks, there is a clear performance saturation phenomenon after models reach a certain scale, where continued increases in parameter count or training data yield rapidly diminishing marginal contributions to accuracy.69% similarUnverifiedAs model parameters scale from hundreds of billions to trillions, the performance gains delivered by each additional order of magnitude of compute become increasingly marginal — a phenomenon the academic community calls the 'ceiling effect' of Scaling Laws.68% similar
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