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
09:42, 9 марта 2026Россия
。关于这个话题，新收录的资料提供了深入分析
“From a business perspective, yeah, I do think Nitra is going to be a decacorn.”
Russell Brandom，更多细节参见新收录的资料
По его словам, Киев, таким образом, стремится избежать повторений формулировок Будапештского меморандума. Кислица считает, что документ содержал лишь заверения, а не реальные гарантии.。关于这个话题，新收录的资料提供了深入分析
如何在这个常态中，进一步激发闲置资产的价值？