A teacher in class explains the difference between 'dog' and 'tog': put your hand on your throat and feel the vibration. A speech recognition machine does much the same thing, except inside it's not a throat but long lists of numbers. It turns out these numbers can be sorted onto shelves, like alphabet blocks in a child's room.

Scientists took a model trained on 96 languages and found directions inside it that correspond to individual sound features. For example, there's a 'voicing' direction. If you take the vector for 'p' and add this vector, you get 'b'. If you add not the whole vector but half of it, you get a sound that's half-voiced, as if the speaker started to whisper but didn't finish.

This discovery has practical value. If we understand how sounds are organized inside the model, we can better tune speech recognition for rare languages with few recordings. Or make voice assistants less likely to confuse 'cot' and 'got' in accented speech. The model has essentially been handed a phonetic atlas, and now it can travel through it deliberately, not by feel.