Count the number of occurrences of the letter e in the word "enterprise".
Problems can exist as instances of a class of problems. If you can't solve a problem, it's useful to know if it's a one off, or if it belongs to a larger class of problems, and which class it belongs to. In this case, the strawberry problem belongs to the much larger class of tokenization problems - if you think you've solved the tokenization problem class, you can test a model on the strawberry problem, with a few other examples from the class at large, and be confident that you've solved the class generally.
It's not about embodied human constraints or how humans do things; it's about what AI can and can't do. Right now, because of tokenization, things like understanding the number of Es in strawberry are outside the implicit model of the word in the LLM, with downstream effects on tasks it can complete. This affects moderation, parsing, generating prose, and all sorts of unexpected tasks. Having a workaround like forcing the model to insert spaces and operate on explicitly delimited text is useful when affected tasks appear.
Problems can exist as instances of a class of problems. If you can't solve a problem, it's useful to know if it's a one off, or if it belongs to a larger class of problems, and which class it belongs to. In this case, the strawberry problem belongs to the much larger class of tokenization problems - if you think you've solved the tokenization problem class, you can test a model on the strawberry problem, with a few other examples from the class at large, and be confident that you've solved the class generally.
It's not about embodied human constraints or how humans do things; it's about what AI can and can't do. Right now, because of tokenization, things like understanding the number of Es in strawberry are outside the implicit model of the word in the LLM, with downstream effects on tasks it can complete. This affects moderation, parsing, generating prose, and all sorts of unexpected tasks. Having a workaround like forcing the model to insert spaces and operate on explicitly delimited text is useful when affected tasks appear.