Larry Greenmeier of Scientific American recently wrote, “As computers have matured over time, the human brain has no way of keeping up with silicon’s rapid-fire calculating abilities. But the human cognitive repertoire extends far beyond just fast calculations. For that reason, researchers are still trying to develop computers that can recognize, interpret and act upon information—like the kind pulled in by eyes, ears, nose and skin—as quickly and efficiently as good old-fashioned gray matter. Such cognitive systems are critical to transforming waves of big data collected by sensor networks into a meaningful representations of, say, automobile traffic on a particular roadway or maritime weather conditions.”

He continues, “There are several efforts underway worldwide to build “neuromorphic” systems that mimic the human brain. IBM, in particular, has made significant strides in this area. In 2011, the company’s Watson system put two former Jeopardy! champs in their place by interpreting questions and quickly finding the answers in its database. A lower-profile—but perhaps more significant—event occurred later that year, when IBM and Cornell University introduced an experimental chip designed to become the building block of a computing system that emulates the brain’s function, efficiency and compact size.”

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