Unverified50% confidenceFactExact time
The current mainstream paradigm centers on the Scaling Law—simultaneously expanding parameters, data and compute yields predictable performance gains.
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10/21/2026
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VerifiedScaling Law refers to the predictable and regular improvement in model capability as the number of parameters and the volume of training data increase.78% similarUnverifiedImproving model capabilities through larger parameters, more data, and greater computing power (Scaling Law) remains one of the core strategies of major laboratories.76% similarUnverified模型效率优化正在成为与规模扩张同样重要的竞争维度71% similarUnverifiedThe core finding of the Chinchilla scaling law is that under a fixed compute budget, simultaneously increasing model parameters and training data volume is required to achieve optimal performance.69% similar
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