This is neat, but most people are going to miss "GPT-3 (babbage-002)". Using a rudimentary, outdated model seems disingenuous when making any kind of point about AI.
Yeah I would say it actually makes the contrary point. That pre hype version of the GPT is poor and if you have to use this one to prove a point it probably means there is a huge jump between GPT3 and GPT4. So to me it proves the contrary. And anybody going for that or believing it doesn't actually understand the performance of GPT4 or better if they are thinking that this is post hype LLM output.
See this comment [0] on this very post, showing how it makes quite problematic mistakes on larger numbers still.
It's still improvement, but only in the way of imitation. It shows that while clever within their constraints, these models still don't have the capabilities to truly perform computation or "thought". Chain of thought can help, but you there are some things you cannot split into atomic tasks; if the very world model isn't that stellar, no amount of elucidation will compensate for the inaccurate representations within. (i.e. "How would person X react to Y?" If your theory of mind is poor, no amount of further subtasks will help you give a better prediction.)