I think the sentiment that simplicity is good, is a false conclusion. Simplicity is simply good scientific methodology.

Doing too many things at once makes methods hard to adopt and makes conclusions harder to draw. So we try to find simple methods that show measurable gain, so we can adapt it to future approaches.

Its a cycle between complexity and simplicity. When a new simple and scalable approach beats the previous state of art, that just means we discovered a new local maxima hill to climp up.