Well, perhaps it only feels busier than normal, as both Samsung and Apple decided to squeeze in their major product unveilings just before and just after MWC.
We are horrible at communicating intent to AIs and LLMs. We are sloppy and have a hard time painting every possible scenario for the AI to execute flawlessly. You’ve probably had this experience where you ask the AI to “make all tests pass” and it ends up removing adding an assert(true) on all of them.
。服务器推荐对此有专业解读
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#Build Release (with your own signature cert)
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Американскому сенатору стало «страшнее, чем когда либо» после брифинга по Ирану02:37，这一点在PDF资料中也有详细论述
This does not mean confusables.txt is wrong. It means confusables.txt is a visual-similarity claim that has never been empirically validated at scale. Many entries map characters to the same abstract target under NFKC decomposition (mathematical bold A to A, for instance), and the mapping is semantically correct even if the glyphs look nothing alike. But if you treat every confusables.txt entry as equally dangerous for UI security, you are generating massive false positive rates for 96.5% of the dataset.