[goodside]

In my tests GPT-3.5 just isn’t smart enough to parse the hidden text encoding. It’s encoded in a way that’s programmatically trivial to convert to ASCII but text written this way usually only occurs inside country flag emojis and always encodes country codes. There is also a deprecated usage for encoding the language of text but these would still only be country codes. It’s likely other people have discovered this method for hiding text in non-AI-related contexts, and have hidden enough of it in publicly available texts that the model can learn it in pre-training. But this is all speculation.

[treprinum]

Aren't GPT-4 and GPT-3.5 using the same tiktoken cl100k_base tokenizer? So in theory they should understand the same input.

[goodside]

It’s not just a matter of the tokenization being the same, it’s whether the model can understand text that’s written with a very rarely seen encoding. Normally tokens represent entire words or portions of words, but in this case it’s not only broken into letters but into bytes, with two full tokens dedicated to every character. Text encoded this way is common (in flag emojis) but extremely lacking in diversity because it only encodes country codes. It’s unclear whether GPT-4 learned this ability by generalizing from country codes or through exposure to steganographic Unicode text on the web. Probably a combination of the two.