Recent advances in deep machine learning let us teach our machines things like how to distinguish classes of inputs and to fit curves to time data. This lets our machines “know” whether an image is that of a cat or not, or to “know” what is about to fail as the temperature increases in a particular sensor inside a jet engine. But this is only part of being intelligent, and Moore’s Law applied to this very real technical advance will not by itself bring about human level or super human level intelligence.Gary Marcus has also been writing on the topic, such as this piece from October 24 at the New Yorker: "Why We Should Think About the Threat of Artificial Intelligence":
Barrat's core argument, which he borrows from the A.I. researcher Steve Omohundro, is that the drive for self-preservation and resource acquisition may be inherent in all goal-driven systems of a certain degree of intelligence. In Omohundro's words, "if it is smart enough, a robot that is designed to play chess might also want to be build a spaceship," in order to obtain more resources for whatever goals it might have.Marcus chats with Russ Robert on his Econtalk podcast posted Dec. 15.