Genetic algorithms is a sort of broad category and there’s certainly ways you could federate and parallelize. I think autoML basically applies this within the ML space (multiple trainings explore a solution topology and convergence progress is compared between epochs, with low performers dropping out). Keep in mind, you can also use a genetic algorithm to learn how to explore an old fashioned state tree.
I think if you can actually define reasoning, your comments (and those like yours) would be much more convincing. I’m just calling yours out because I’ve seen you up and down in this thread repeating it, but it’s a general observed of the vocal critics of the technology overall. Neither intelligence nor reasons (likewise understanding and knowing, for that matter) are easily defined in a way that is more useful than invoking spirits and ghosts. In this case, detecting patterns certainly seems a critical component of what we would consider to be reasoning. I don’t think it’s sufficient, buy it is absolutely necessary.