Simple is good. Especially in machine learning where a bug usually means that it kinda works, but not as well as it could. Also, when an off-the-shelf algorithm half works, it's good to be able to add you own tweaks to it, and again, this requires simplicity.

For a complicated architecture to succeed, it's going to need to reliably achieve state of the art performance on everything without requiring any adjustment or tweaks.