I was studying evolutionary computation back in the 80s. Yes, you did not have the large ANNs you have today, but you also broke down your problem into manageab

I was studying evolutionary computation back in the 80s. Yes, you did not have the large ANNs you have today, but you also broke down your problem into manageable, computable bits (no pun intended). Working through Koza's book on Genetic Programming in the 90s, or Mark Watson's book on ANNS, chaos theory, and a bunch of other stuff, was very illuminating. I particularly liked the artificial life stuff out of the Santa Fe Institute. I still have a VHS from the 2nd proceedings. I could have rode the ML/DL wave to a high salary job, but I took another path building real-world objects and machines, and I am very happy I did. I remember when WordPerfect was popular and people spoke of careers in wordprocessing. I always saw it as evolution of the cube farm, and of course, it is. Now I have friends who work in industry with ML/DL, and they joke that it's the same but with a lot more things to track and keep running. I like GOFAI for the simple matter that sometimes 90% is good enough, and 125% is a waste of time, water in the blender. When robotics was taking off I saw the two schools of thought: Rodney Brooke's subsumption architecture making it simple to create emergent behavior, and Mark Tilden's analog circuits and discrete components. I found Tilden's work more interesting. It spoke to me about continuous or biological-like processes. I am now into researching neurocomputing and following the developments in designing neurocomputing hardware. I was so happy to have received free tickets to watch Terminator 2 back in the day, but now I feel like I have a front-row seat to it!