Unverified60% confidenceFactExact time
Large language models typically have parameter counts in the tens to hundreds of billions, which exceeds the VRAM and compute capacity of a single personal device for full inference.
2
Sources
60%
Confidence
Long-term
Relevance
7/12/2026
First Seen
Sources
AI Coding Tool Data Leakage Risks: A Security Guide for Protecting Quantitative Strategies
bilibili国金证券宜宾营业部7/8/2026
Related Claims
UnverifiedThe value orientations, knowledge boundaries, and safety mechanisms of large language models are embedded in hundreds of billions of parameters, making them difficult to externally audit or independently verify78% similarVerified大语言模型推理的瓶颈往往不在计算能力,而在于内存带宽76% similarUnverifiedFor agents based on large language models, intrinsic interpretability is nearly unattainable, because the nonlinear interactions of billions of parameters cannot be directly interpreted by humans.75% similarUnverifiedTraditional autoregressive language models sample from the entire vocabulary (typically tens of thousands to hundreds of thousands of tokens) or select the highest-probability token during generation.74% similarUnverified大语言模型的用量计费通常基于token(词元)消耗,而非简单的对话次数74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/488960API
curl https://kongchang.com/api/v1/knowledge/claims/488960MCP
get_claim(id=488960)