Unverified50% confidenceFactExact time
Traditional large language models work as single-turn or multi-turn input-to-output conversations and inherently lack the ability to perceive external environments, call tools, or continuously execute steps.
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50%
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Long-term
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9/24/2026
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Related Claims
UnverifiedLarge language models do not require predefined intent classification, can understand open-domain expressions, and handle multi-turn conversations through a context window.78% similarUnverifiedIn multi-agent systems, collaboration among large language models has long relied on converting one model's output into natural-language text and feeding it as a prompt to the next model.76% similarUnverified大语言模型每次对话独立，无法对整个代码库形成持久认知模型，导致不同会话生成的代码在架构风格、命名规范、错误处理策略上存在系统性不一致76% similarUnverifiedTraditional interfaces are designed for programs and lack the semantic context required by large models; large models need tool wrappers with natural language semantic descriptions to invoke them correctly.76% similar
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