Unsupervised Machine Learning Could Help Us Solve the Unsolvable

In machine learning, the ultimate goal is to train a machine or computer to learn and infer like a human, taking into account much more information and making better decisions in exponentially less time than humans are able to do. While the potential applications of machine learning multiply daily, the time and effort required to train optimized machine learning systems is substantial and, as voiced by Dr. Yoshua Bengio in a recent interview, constant training and feeding of information is not a “natural” way to learn and obtain knowledge. All of these factors point to the invaluable potentials of unsupervised learning, which if done successfully can learn and infer largely without the aid of a human. Only within the last decade has machine learning gained a foothold, thanks to the…


Link to Full Article: Unsupervised Machine Learning Could Help Us Solve the Unsolvable