I gave ChatGPT some miswritten Braille a while ago and it completely, but confidently, messed it up. The sign reads "no smoking" but the braille doesn't. ChatGPT 1) read the English lettering first and then hallucinated the braille and the 2) when given only the braille, failed almost as hard. It even generated fake transcriptions in Unicode braille characters.
Annoying. The actual braille on the sign was "⠁⠒⠑⠎⠎⠊⠼" which I gather means "accessible" in abbreviated braille. None of my attempts got it to even transcribe it to Unicode characters properly. I got "elevator", "friend", etc. Just wildly making stuff up and completely useless, even when it wasn't distracted by the No Smoking sign (in the second case I cropped out the rest of the sign). And in all cases, supremely confident.
This seems like something a VLM should handle very easily, but instead I got pure nonsense.
> This seems like something a VLM should handle very easily
Not if its training data doesn't include braille as first class but has lots of braille signage with bad description (e.g., because people assumed the accompanying English matches the braille.)
This could very well be the kind of mundane AI bias problem that the x-risk and tell-me-how-to-make-WMD concerns have shifted concerns about problems in AI away from.
I'd wager that correctly labeled braille far exceeds dumb braille, and when presented with just the braille it flat out hallucinated braille characters that weren't there. It didn't seem to actually be parsing the dots at all. My theory is that it has hardly seen any braille, despite it insisting that it knows how to read it.
https://chatgpt.com/share/683f3e7d-0dfc-8005-b6c9-99e3d39ff4...
https://chatgpt.com/share/683f3e49-9c58-8005-99a6-c3a919838b...