Are Better Machine Training Approaches Ahead?

We live in a time of unparalleled use of machine learning (ML), but it relies on one approach to training the models that are implemented in artificial neural networks (ANNs) -- so named because they're not neuromorphic. But other training approaches, some of which are more biomimetic than others, are being developed. The big question remains whether any of them will become commercially viable. ML training frequently is divided into two camps -- supervised and unsupervised. As it turns out, the divisions are not so clear-cut. The variety of approaches that exists defies neat pigeonholing.