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Why Large Language Models Can’t Be Trusted with the Truth
The more convincing the delivery, the easier it is to overlook the cracks in the foundation.
LLMs become most dangerous precisely when they sound most right. In information‑hungry environments, a confident error often outranks a cautious truth.
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