the move from "software engineering" to "AI engineering" is basically a switch from a hard science to a soft science.
rather than being chemists and physicists making very precise theory-driven predictions that are verified by experiment, we're sociologists and psychologists randomly changing variables and then doing a t-test afterward and asking "did that change anything?"
the difference is between having a "model" and a "theory". A theory tries to explain the "why" based on some givens, and a model tell you the "how". For engineering, we want why and not how. ie, for bugs, we want to root-cause, and fix - not fix by trial-and-error.
the hard sciences have theories. and soft sciences have models.
computer science is built on theory (turing machine/lambda calc/logic).
AI models are well "models" - we dont know why it works but it seems to - thats how models are.
the move from "software engineering" to "AI engineering" is basically a switch from a hard science to a soft science.
rather than being chemists and physicists making very precise theory-driven predictions that are verified by experiment, we're sociologists and psychologists randomly changing variables and then doing a t-test afterward and asking "did that change anything?"