At my job, there is a problem that's classically solved with a bunch of regexps and run of the mill text parsing. The ML experts in my company keep telling me

At my job, there is a problem that's classically solved with a bunch of regexps and run of the mill text parsing. The ML experts in my company keep telling me maintaining these regexps is too costly dev wise, and that they can use ML to adapt to changes in the real world, and get a better result faster. After nearly a year of work, buying some fancy new computers with giant GPUs, and countless meetings to describe the problem space, they have something that's around 60-70% as accurate as the current state of the art, and say they're close to closing the gap. Meanwhile I add a new regexp or tweak an existing one and cause them to go back to the drawing board because I've "changed the entire problem description". Sometimes I feel like I want the job where the only criteria is that I'm using the fancy new toys. It seems like more fun.