Expired65% confidenceOpinionTime unknown
Entering 2025, the industry has broadly observed that the marginal returns of Scaling Laws are diminishing, and the capability gains from simply increasing model size are no longer as significant as in earlier stages.
3
Sources
65%
Confidence
Medium-term (~90 days)
Relevance
6/1/2026
First Seen
Valid until: 8/30/2026(expired)
Sources
Related Entities
Related Claims
UnverifiedStarting from 2024, the industry has observed diminishing returns from simply scaling up model size, particularly on tasks such as multi-step logical reasoning, mathematical proofs, and scientific discovery.81% similarUnverified大模型存在时效性衰减问题，若未接入实时数据源，其输出的市场趋势判断可能滞后数月乃至一年以上72% similarUnverifiedThe marginal returns of simply increasing model parameters and training data are diminishing, a phenomenon known as 'Scaling Law slowdown.'71% similarUnverifiedJob-hopping is only justified when at least one of the following conditions holds: repetition outweighs growth, compensation is significantly below market, or there is a clear new goal.70% 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.70% similar
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