Unverified50% confidenceFactExact time
The corresponding core concepts in AI are generalization and out-of-distribution reasoning; a model performing well within its training distribution does not guarantee it can handle novel problems not encountered during training.
1
Sources
50%
Confidence
Long-term
Relevance
10/9/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedCapability-related risks in AI models are not like patchable CVE vulnerabilities; offensive capabilities are part of the training outcome and cannot be completely eliminated through a single update.76% similarUnverifiedA code of conduct alone cannot resolve AI safety issues; whether a model deceives humans is often the result of the combined effect of training data, optimization objectives, and deployment environment.75% similarUnverified领域知识与ML能力的组合是纯AI背景者所欠缺的，行业经验在垂直领域AI应用中构成差异化竞争力75% similarUnverifiedBecause AI generative models lack explicit modeling of physical laws in their training data, their outputs often violate real physical laws at the detail level.75% similarUnverifiedThe vast majority of frontier AI models do not fully disclose the composition of their training datasets, citing reasons including trade secrets, legal risks, and the enormous scale of the data.75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/991119API
curl https://kongchang.com/api/v1/knowledge/claims/991119MCP
get_claim(id=991119)