My favourite example of this type of thing isn't mentioned in the article - using evolutionary computing to do some of the things mentioned in said article:
I read that paper about 20 years ago - at the time I was very interested in ML, and was torn between neural networks and evolutionary algorithms. This paper caused me to go all in on evolutionary algorithms, and eventually burn out because I could never get any kind of promising result out of it. Wrong choice I guess!
Yeah, I tried my hand at some evolutionary algorithms and found it's all about the fitness function. I'd spend hours and hours refining it and eventually realized that you're really just optimizing the function to fit what you want to see. Kinda took the magic out of it for me.
> 20 years ago... This paper caused me to go all in on evolutionary algorithms, and eventually burn out because I could never get any kind of promising result out of it. Wrong choice I guess!
Wow. 36 years ago, I was super excited about neural networks, but lacked the skill to get good results fast enough; meanwhile, a very talented colleague was getting really interesting results from evolutionary algorithms.