Стало известно об изменении военной обстановки в российском приграничье08:48
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Something that used to come naturally is now a subject of longing and fascination, as if it were a rare anthropological phenomenon. Videos are springing up on social media, cataloguing encounters with the unknown “other”: earnest, well-meaning, wholesome videos, under the categories “social anxiety”, “extrovert” and “talking to strangers”. Many have the unstated theme of “out and about in the big city”. Some are personal experiments, often extremely ill-advised ones. Can you challenge yourself to tell a joke to an entire train carriage? What happens if you go up to an older woman and tell her she looks beautiful? The (usually young) person doing the filming is often trying to improve themself in some way or attempting to “be braver” or “less socially anxious”. The camera acts as their accountability partner. The people they’re talking to are relegated to the role of “task to be ticked off the list”. Either that or there’s a push towards a Hallmark card effect: “Look, other people are not as horrible as you thought.” (Cue swell of trending motivational audio.)。关于这个话题，体育直播提供了深入分析
We propose sycophancy leads to less discovery and overconfidence through a simple mechanism: When AI systems generate responses that tend toward agreement, they sample examples that coincide with users’ stated hypotheses rather than from the true distribution of possibilities. If users treat this biased sample as new evidence, each subsequent example increases confidence, even though the examples provide no new information about reality. Critically, this account requires no confirmation bias or motivated reasoning on the user’s part. A rational Bayesian reasoner will be misled if they assume the AI is sampling from the true distribution when it is not. This insight distinguishes our mechanism from the existing literature on humans’ tendency to seek confirming evidence; sycophantic AI can distort belief through its sampling strategy, independent of users’ bias. We formalize this mechanism and test it experimentally using a rule discovery task.，详情可参考体育直播
「唐納德·特朗普正把美國拖入美國人民不想要的戰爭，」美國前副總統暨2024年民主黨提名人賀錦麗（Kamala Harris）在聲明中說。她補充：「我們的部隊正為了特朗普的選擇性戰爭而置於險境。」