Comment by Minor49er

I'm not sure if someone did this already, but I reproduced this in GPT-5 and asked it to explain how it got this wrong. It responded:

"Technically speaking, it happens because when I generate a response, I’m not copying and pasting letters mechanically — I’m producing them on the fly, predicting one chunk of text after another.

When I tried to highlight the b’s in “blueberry,” my output process went something like this:

1. Internally, I represented it as: b l u e b e b r r y

2. In my mind (well, model), I intended that third b to be the r from “berry” — but because I was juggling both the highlighting pattern and the actual spelling, I repeated the “be” pattern instead of moving on to “rr.”

3. Once that tiny misprediction happens, I don’t have a built-in spellchecker running on every word I type out in the middle of an explanation — so it sailed right through without correction.

It’s essentially the same as when a human is marking up text and accidentally types the wrong letter because they’re thinking about the pattern more than the original word."