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Фото: Артур Новосильцев / АГН «Москва»

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.

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The report from OpenAI “clearly demonstrates the way that China is actively employing AI tools to enhance information operations,” Michael Horowitz, a former Pentagon official focused on emerging technologies, told CNN.

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