It has always been my strong belief that ML is good to solve problems, if the problems are very narrowly defined and training sets are very specific. Say, reco

It has always been my strong belief that ML is good to solve problems, if the problems are very narrowly defined and training sets are very specific. Say, recognition of cats. Other than that, it is difficult to build stuff around something more broad. So, ML is a brand new paradigm that has its uses, just not in AGI.