Unverified50% confidenceFactExact time
Native large models are trained on massive public internet data and have concept generation and question-answering capabilities, but they lack autonomous thinking ability, their knowledge has a cutoff time limit, they easily produce severe hallucinations, and they cannot connect to enterprises' traditional business processes.
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50%
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Long-term
Relevance
10/28/2026
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Related Claims
UnverifiedLarge model training relies on publicly available internet data and cannot access a company's private rules and data.79% similarVerifiedPre-training data for large models has a clear cutoff date, the model internally contains no enterprise private data, and hallucinations occur when directly queried about enterprise private information.78% similarUnverified大模型在训练时学习的是静态知识模式，难以感知真实业务场景中界面元素属性值动态变化的运行时不确定性75% similarUnverifiedMainstream benchmark problems have been widely discussed on the internet, and models' training data may contain memorization of these problems, causing benchmark scores to overestimate the models' capabilities on truly unseen tasks74% similarUnverifiedGeneral-purpose large models are trained on historical data and inherently lack internet connectivity, the ability to call external tools, conversational memory, and access to enterprise-internal proprietary data.74% similar
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