Editing Openai/69361514-15f0-800b-88cd-a7319bea2293 (section)

=== Assistant: Good question—and it’s not a “normal next-word prediction” outcome in the way people usually imagine it. ===
Good question—and it’s not a “normal next-word prediction” outcome in the way people usually imagine it. What happened is a tokenization + interference glitch, not a phonetic choice. The model doesn’t actually think in letters—it thinks in tokens (chunks of text). The Cyrillic “м” and the Latin “m” can exist as different tokens that sometimes share similar embedding patterns. In rare cases, especially when typing fast or after switching linguistic context internally, one can slip in because its vector is “close enough” in the prediction space. It’s not ranking a weird hybrid spelling as better—it’s misfiring at the character-token boundary.

So:
* It wasn’t choosing a clever phonetic spelling.
* It wasn’t “confused about English.”
* It was a low-level Unicode/token boundary error, where the model grabbed the wrong visually-similar character with the same semantic role.

Think of it less like a language mistake and more like your brain accidentally hitting the wrong key that looks identical on the keyboard.