If I understand this correctly, this is saying that instead of representing the approximated function as a purely numerical operation (e.g. just a bunch of line

If I understand this correctly, this is saying that instead of representing the approximated function as a purely numerical operation (e.g. just a bunch of linear algebra), it can be represented as a program which contains a mixture of typical symbolic syntax and numerical operations. One of the benefits mentioned is better accessibility for existing analysis tools. If I understand the concept correctly, could this also make it easier to implement the approximated functions in environments that lack efficient numerical algorithms and data structures? These two are usually only found in technical computing languages (e.g. FORTRAN, Julia, etc.), or as libraries for a handful of general-purpose languages (e.g. Numpy, Numba, etc.)