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
生态环境部党组提出，认真落实学习研讨、查摆问题、整改整治、建章立制、开门教育等工作安排，教育引导部系统各级党组织和全体党员干部坚持实事求是、求真务实，坚决有力贯彻落实党中央重大决策部署，为人民出政绩、以实干出政绩，为推动美丽中国建设取得新的重大进展提供有力保障。。新收录的资料对此有专业解读
Another version of BusinessWeek Business Advantage via The Mac Attic，这一点在新收录的资料中也有详细论述
Developers losing their ability to distribute apps across all channels due to a single un-reviewable corporate decision，详情可参考新收录的资料