Иран установил личности виновных в ударе по школе для девочек в Минабе14:56
I guess I should have seen this coming. I knew the best way to understand these models was as simulators, and I may have fallen into a version of the immersive fallacy.
PROOF: https://reut.rs/4smh6Zo I will answer questions from 11 a.m.-12 p.m. ET，详情可参考91视频
Глава управления аналитики по рынкам ценных бумаг Альфа-банка Борис Красноженов полагает, что биржевые цены на золото могут пробить очередную психологическую отметку на фоне эскалации конфликта на Ближнем Востоке. С учетом общей экономической неопределенности золото останется главным «активовом-убежищем». В случае затягивания войны в Иране, не исключил Красноженов, котировки драгметалла могут достичь новых исторических максимумов.，这一点在Safew下载中也有详细论述
Ранее адвокат по уголовным делам, партнер Московской коллегии адвокатов «Вектор Прайм» Альберт Халеян предположил, что Руслану Цаликову может грозить до 20 лет лишения свободы.，更多细节参见PDF资料
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.