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Cognitive computing describes technologies that are based on the scientific principles behind artificial intelligence and signal processing, encompassing machine self-learning, human-computer interaction, natural language processing, data mining and more. Its aim is to solve complex problems characterized by uncertainty and ambiguity, which in other words means problems that are only solved by human cognitive thought.
Cognitive computing is the branch of computer science concerned with solving complex problems that may have dynamically shifting situations and information-rich data that tend to frequently change and sometimes even conflict with each other. A human may deal with such problems by evolving goals and changing objectives, but traditional computing algorithms are not able to adapt to such change. In order to deal with these sorts of problems, cognitive computing systems have to weigh the conflicting data and suggest an answer that best fits the situation rather than what is "right."
Though there is currently no agreed-upon definition of cognitive computing in the industry or the academe, the term is often used to describe new technology that mimics the way that the human brain functions and how it approaches problem solving. It can be seen as a field that has a goal of accurately modeling how the human mind senses, reasons and responds to stimuli around it. Its greatest applications would be in data analysis and adaptive output, adjusting output to fit a particular audience.
Properties of a cognitive computing system include: