No, it's a rebuttal of what you said: CoT is not making up for a deficiency in tokenization, it's making up for a deficiency in transformers themselves. These complexity results have nothing to do with tokenization, or even LLMs, it is about the complexity class of problems that can be solved by transformers.
There's a really obvious way to test whether the strawberry issue is tokenization - replace each letter with a number, then ask chatGPT to count the number of 3s.
Count the number of 3s, only output a single number:
6 5 3 2 8 7 1 3 3 9.
No, it's a rebuttal of what you said: CoT is not making up for a deficiency in tokenization, it's making up for a deficiency in transformers themselves. These complexity results have nothing to do with tokenization, or even LLMs, it is about the complexity class of problems that can be solved by transformers.
There's a really obvious way to test whether the strawberry issue is tokenization - replace each letter with a number, then ask chatGPT to count the number of 3s.
Count the number of 3s, only output a single number: 6 5 3 2 8 7 1 3 3 9.
ChatGPT: 3.