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Малышева отчитала гостью ее передачи и предрекла ей инсульт14:53
People increasingly use large language models (LLMs) to explore ideas, gather information, and make sense of the world. In these interactions, they encounter agents that are overly agreeable. We argue that this sycophancy poses a unique epistemic risk to how individuals come to see the world: unlike hallucinations that introduce falsehoods, sycophancy distorts reality by returning responses that are biased to reinforce existing beliefs. We provide a rational analysis of this phenomenon, showing that when a Bayesian agent is provided with data that are sampled based on a current hypothesis the agent becomes increasingly confident about that hypothesis but does not make any progress towards the truth. We test this prediction using a modified Wason 2-4-6 rule discovery task where participants (N=557N=557) interacted with AI agents providing different types of feedback. Unmodified LLM behavior suppressed discovery and inflated confidence comparably to explicitly sycophantic prompting. By contrast, unbiased sampling from the true distribution yielded discovery rates five times higher. These results reveal how sycophantic AI distorts belief, manufacturing certainty where there should be doubt.，推荐阅读电影获取更多信息
Акция протеста прошла у посольства Украины в стране ЕС20:39，更多细节参见纸飞机下载
Nature, Published online: 25 February 2026; doi:10.1038/s41586-026-10150-1，推荐阅读一键获取谷歌浏览器下载获取更多信息
China may see this as a chance to "look for cues", says Shetler-Jones, on how Trump may respond to other flashpoints like Taiwan, the self-governed island it claims.