Unverified50% confidenceOpinionExact time
VRAM requirements do not grow linearly; each time a model scale threshold is crossed, the required VRAM jumps up by a step.
1
Sources
50%
Confidence
Long-term
Relevance
10/18/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedWhen model scale exceeds a certain threshold, certain capabilities suddenly jump from near zero to a significant level, rather than growing linearly with parameter count.78% similarUnverified近似遗忘通过梯度上升等方法主动削弱特定数据对模型参数的影响，但效果难以量化验证76% similarUnverified数据规模的增长并不等同于有效学习信号的增长，在模型能力提升到一定阈值后简单堆砌样本的收益会急剧下降75% similarUnverifiedWhen model scale crosses certain thresholds, emergent capabilities not previously present arise (emergent abilities), such as multi-step logical reasoning and complex mathematical computation.74% similarVerifiedEmergent ability refers to the phenomenon where, once a model's scale exceeds a certain critical threshold, certain previously absent capabilities suddenly appear and performance undergoes a sharp leap.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1058475API
curl https://kongchang.com/api/v1/knowledge/claims/1058475MCP
get_claim(id=1058475)