Machine Learning (ML) is a programming technique in which statistical algorithms are applied to large collections of data, commonly using the framework of Artificial Neural Networks. Today, ML applications are ubiquitous and already credited with changing the way we live in many ways. Clearly it is here to stay. Machine Learning’s successes have been so widely publicized that the term has been become nearly synonymous with Artificial Intelligence.
Many experts do in fact believe that this technique many be improved without limit to create programs that will someday achieve human-level or even super-human intelligence. This belief has been widely publicized by the media to the point that the expectation that machines with human-like comprehension and common sense are just around the corner is widespread in the general public.
But Machine Learning, today has some fundamental limitations even in the areas where it has had its greatest successes. Increasingly, these limitations are being recognized by some of the most influential minds in the field.