Unverified50% confidenceBenchmarkExact time
投机采样通过小型草稿模型生成候选token由大模型并行验证，可在不损失质量前提下将吞吐提升2-3倍
1
Sources
50%
Confidence
Long-term
Relevance
7/11/2026
First Seen
Sources
AI's Second Half: The Decisive Battle Shifts from Models to Infrastructure
hackernewshackernews7/9/2026
Related Claims
UnverifiedThe quality of synthetic data is highly dependent on prompt design and the quality of the original documents; using the same model to generate data and serve as an evaluation benchmark carries the risk of self-reinforcing bias, and the best practice is to mix it with human-annotated data and validate through A/B testing.72% similarUnverified3次以上的独立采样才能提供足够的方差估计，是生产级提示词评估流程中被广泛采用的最佳实践71% similarUnverified项目内置生成—评估—重试机制，最多3次重试，若三次均不达标则返回最匹配版本70% similarUnverified3 次以上的独立采样才能提供足够的方差估计，使创意评估从运气判断升级为概率判断，是生产级提示词评估的最佳实践70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/484798API
curl https://kongchang.com/api/v1/knowledge/claims/484798MCP
get_claim(id=484798)