Now back to reality, LLMs are never that good, they're never near that hypothetical "I'm feeling lucky", and this has to do with how they're fundamentally designed, I never so far asked GPT about something that I'm specialized at, and it gave me a sufficient answer that I would expect from someone who is as much as expert as me in that given field. People tend to think that GPT (and other LLMs) is doing so well, but only when it comes to things that they themselves do not understand that well (Gell-Mann Amnesia2), even when it sounds confident, it may be approximating, averaging, exaggerate (Peters 2025) or confidently (Sun 2025) reproducing a mistake. There is no guarantee whatsoever that the answer it gives is the best one, the contested one, or even a correct one, only that it is a plausible one. And that distinction matters, because intellect isn’t built on plausibility but on understanding why something might be wrong, who disagrees with it, what assumptions are being smuggled in, and what breaks when those assumptions fail
樊董伟：落实每天两小时体育活动，我们遇到的最大障碍是来自家长的不理解。要破局，关键还是要改变评价机制。如果体育在升学过程中占有一定比例，大家自然会重视。
。新收录的资料对此有专业解读
“总书记，您平时这么忙，还来看我们，真的感谢您。”朴实的村民由衷地说。
Фото: Максим Богодвид / РИА Новости
，更多细节参见新收录的资料
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全国人大代表、浙江中医药大学附属第三医院院长助理陈玮。受访者供图，推荐阅读新收录的资料获取更多信息