I presently receive files from a device in a semi-csv format. I have a written a simple recursive descent parser for getting information out of these files. Every time the device updates firmware, I have a new version of the parser for the changes the update brings.
Down the road, we will be taking data from other devices, which means another parser and more updates to firmware. I'm wondering if I could define a basic structure of "this is the data I need" and use a neural network to get the parsed data without having to write a parser for each new file type that comes in.
Is this a pipe dream or is it a valid application of machine learning? I'm much more of a software engineer than I am a data scientist, but I'm starting to dip my toes into the machine learning realm.
Thanks in advance.