Yeah this article gets a whole bunch of history wrong.

Back in 2000s, the reason why nobody was pursuing neural nets was simply due to compute power, and the fact that you couldn't iterate fast enough to make smaller neural networks work.

People were doing genetic algorithms and PSO for quite some time. Everyone knew that multi dimentionality was the solution to overfitting - the more directions you can use to climb out of valleys the better the system performed.