This weakness in ChatGPT and its siblings isn't surprising when viewed in light of how these large language models work. They don't actually "see" the things we type as a string of characters. Instead, there's an intermediate step where what we type gets turned into "tokens." Tokens are basically numbers that index words in a giant dictionary that the LLM knows. So if I type "How do you spell apple?" It gets turned into [2437, 466, 345, 4822, 17180, 30]. The "17180" in there is the token ID for "apple." Note that that token is for "apple" with a lower case; the token for "Apple" is "16108". The LLM "knows" that 17180 and 16108 usually mean the same thing, but that 16108 is generally used at the beginning of a sentence or when referring to the computer company. It doesn't inherently know how they're actually spelled or capitalized unless there was information in its training data about that.

You can play around with OpenAI's tokenizer here to see more of this sort of thing. Click the "show example" button for some illustrative text, using the "text" view at the bottom instead of "token id" to see how it gets chopped up.

For that to work, it would need to create a Python script that would remove all of the words ending with A, run that script, and then give you the results. I think this process of handling user requests is in the works.