>"if the idea was so good, why hasn't anyone commercialized/done this before?"
If researchers are not asking this themselves then they should be drummed out, and if they are asking this and they don't have an answer, and are still doing it, then they should be drummed out. Good people know why things didn't work last time, and they can give you a pin point explanation as to what needs to be done to break the bottleneck and make progress.
Case in point : Hinton and Deep Networks. Training big networks is impractical, you need vast amounts of labelled data, you need vast amounts of compute, the over fit. So - build auto encoding layers, build rectified activation functions, do drop out. Well developed, careful attacks on specific issues.
Another one is what's happening with fusion research at MIT right now : Whyte's attacking scale, attacking containment, attacking ablation. There are specific problems articulated, specific approaches to tackle them. These approaches come with risk, large risk, but it's not "because this time it's different"