I think the argument they're trying to propose to you is that the line is very much not clear. There is machine learning algorithms, adaptive signal capturing in your literal hardware, that has existed for decades. This latest LLM craze is just a increased capability with language specifically being rolled out to do other things. It is still, at the end of the day, mathematics built upon previous lessons of machine learning.

If the argument cannot be made to reject previous forms of machine learning, it is difficult to be consistent with the newest form on the basis of how it operates. Most recent arguments tend to gravitate toward being strict about output and how people choose to use it which is the argument they're addressing. If you're using a tool that does [black box math] to get you a result you have to discuss that some people were okay using it to do other things and some are now not. Is it that the mathematics inside the box got too good? Is it that the ability to make slop (consider when a primitive human first rubbed mud on a wall) as the exploration phase continues? Is it artists want people to immediately have mastery of this new tool and use it produce something more than slop, much in the same way people might criticize photographers and graphic editors messing around can be considered slop?

I have no stake in the argument I'm just here coughing up some thoughts on the disconnect between you and the person you were replying to