It's worth noting that this may not be result of a pure LLM, it's possible that ChatGPT is using "actions", explicitly:
1- running the query through a classifier to figure out if the question involves numbers or math
2- Extract the function and the operands
3- Do the math operation with standard non-LLM mechanisms
4- feed back the solution to the LLM
5- Concatenate the math answer with the LLM answer with string substitution.
So in a strict sense this is not very representative of the logical capabilities of an LLM.
Then what's the point of ever talking about LLM capabilities again? We've already hooked them up to other tools.
This confusion was introduced at the top of the thread. If the argument is "LLMs plus tooling can't do X," the argument is wrong. If the argument is "LLMs alone can't do X," the argument is worthless. In fact, if the argument is that binary at all, it's a bad argument and we should laugh it out of the room; the idea that a lay person uninvolved with LLM research or development could make such an assertion is absurd.
1- running the query through a classifier to figure out if the question involves numbers or math 2- Extract the function and the operands 3- Do the math operation with standard non-LLM mechanisms 4- feed back the solution to the LLM 5- Concatenate the math answer with the LLM answer with string substitution.
So in a strict sense this is not very representative of the logical capabilities of an LLM.