Verified70% confidenceFactExact time
Native large models have deficiencies such as having no memory, having a knowledge cutoff date, being unable to access the internet, and being unable to operate tools or computers.
4
Sources
70%
Confidence
Medium-term (~90 days)
Relevance
9/15/2026
First Seen
Valid until: 12/14/2026
Sources
Related Entities
Related Claims
UnverifiedNative large language models have three major shortcomings: a lack of continuous reasoning capability, limitations in knowledge timeliness, and the inability to connect with enterprise systems.73% similarUnverifiedA large language model is essentially a stateless function: it has no memory of its own, does not think proactively, and does not invoke tools on its own initiative.70% similarVerifiedThe core capabilities of large language models are reasoning and question answering, but they lack memory and their knowledge has a temporal cutoff at the time of training.66% similarUnverified目前尚无工业级成熟解决方案能在不损害模型性能的前提下实现精确的数据遗忘66% similarUnverifiedWhat blocks AI deployment is not model capability, but four things AI cannot independently resolve: vague requirements, dirty data, fragmented systems, and unaccountable delivery.65% similar
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