Unverified50% confidenceOpinionExact time
The value orientations, knowledge boundaries, and safety mechanisms of large language models are embedded in hundreds of billions of parameters, making them difficult to externally audit or independently verify
1
Sources
50%
Confidence
Long-term
Relevance
9/17/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedLarge language models typically have parameter counts in the tens to hundreds of billions, which exceeds the VRAM and compute capacity of a single personal device for full inference.78% similarUnverifiedLarge language models cannot reliably distinguish the boundary between system instructions and user/external content during inference—this is a fundamental limitation of prompt injection, similar in principle to SQL injection.75% similarUnverifiedCurrent large language models lack an inherent ability to distinguish the source and authority level of information when processing all input within the same context window.74% similarUnverifiedLarge language models possess powerful knowledge integration and reasoning capabilities that could be exploited by malicious actors to lower the barrier to accessing dangerous information.72% similarUnverifiedThe knowledge of large language models comes from training data, primarily from publicly available internet information, and they cannot access enterprise internal data.71% similar
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