Donald Trump ‘really does not care’ if Iran play at World Cup 2026

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Yvette Becker from FNV union says a four‑day working week can help close the gender gap. "You gain productivity with less absenteeism."

«Немыслимо, что он [Зеленский] является препятствием. У вас нет козырей в рукаве. А теперь у него их стало еще меньше», — подчеркнул глава Белого дома.

UK Mulls R,推荐阅读PDF资料获取更多信息

尽管关闭直销渠道,GUESS 在短信中强调「并非退出中国市场」,而是将以全新模式继续深耕。

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.

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