Unverified50% confidenceFactExact time
将年龄字段从100个可能值泛化为5个区间，信息熵从约6.64比特降至约2.32比特，信息量损失超过60%
1
Sources
50%
Confidence
Long-term
Relevance
8/12/2026
First Seen
Sources
Related Claims
UnverifiedShannon estimated the information entropy of English to be approximately 1–1.5 bits per character, far below the theoretical maximum.70% similarUnverified当所有商家评分集中在4.5-4.9的狭窄区间时，评分系统的信息熵急剧下降，用户从评分中获得的有效决策信息趋近于零69% similarUnverified在标准投影方案下，教师分布的熵从2.09 bits骤降至0.32 bits，仅约15%的教师信息得以保留69% similarUnverifiedResearch indicates that when the context exceeds a certain length, the model's recall accuracy for content in the middle portion may drop below 50%.68% similarUnverifiedThe compute cost per unit of inference is declining at a rate of 40% to 60% per year.67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/735405API
curl https://kongchang.com/api/v1/knowledge/claims/735405MCP
get_claim(id=735405)