Why have the LLM do arithmetic at all though? Just have it generate python if you need a calculation.
If the LLM is trained on arithmetic, its arithmetic results could be more accurate than its untested code, due to that being a simpler task with simple rules over a small number of symbols with a fixed meaning.
Situations in which the LLM produces code requires the operator to be a programmer, in order to understand, and test the code, possibly fixing it, and give feedback about it. Someone who just wanted the AI to check some arithmetic doesn't want to be checking the AI's buggy code and may not even know how.
This to me seems much more flexible and likely to work than training a neural network to do arithmetic.
Processing tabular data such as spreadsheets.
Efficiency — invoking Python would be very inefficient for scenarios such as a math tutor AI checking a student’s arithmetic.
Generally I like to think of a useful AI as a hybrid between biological networks and computers. Give an LLM the ability to compute directly so it’s not emulating a human with a calculator, but working more like a human with a calculator neural implant.