Cognitive computing
Cognitive computing (CC) refers to technology platforms that, broadly speaking, are based on the scientific disciplines of artificial intelligence and signal processing. These platforms encompass machine learning, reasoning, natural language processing, speech recognition and vision (object recognition), human–computer interaction, dialog and narrative generation, among other technologies. Definition. At present, there is no widely agreed upon definition for cognitive computing in either academia or industry. In general, the term cognitive computing has been used to refer to new hardware and/or software that mimics the functioning of the human brain (2004) and helps to improve human decision-making. In  this sense, CC is a new type of computing with the goal of more accurate models of how the human brain/mind senses, reasons, and responds to stimulus. CC applications link data analysis and adaptive page displays (AUI) to adjust content for a particular type of audience. As such, CC hardware and applications strive to be more affective and more influential by design. If there is feedback between the actuators and the sensors, the cognitive system can form a digital control loop. Typically, cognitive systems communicate with other systems to exchange, verify or validate data. With appropriate cooperation, multiple systems  can operate simultaneously in the digital and real worlds. Humans can interact with cognitive systems via human-machine interfaces. Some features that cognitive systems may express are: Cognitive analytics. Cognitive computing-branded technology platforms typically specialize in the processing and analysis of large, unstructured datasets. Word processing documents, emails, videos, images, audio files, presentations, webpages, social media and many other data formats often need to be manually tagged with metadata before they can be fed to a computer for analysis and insight generation. The principal benefit of utilizing cognitive analytics over traditional big data analytics is that such datasets do  not need to be pre-tagged. Other characteristics of a cognitive analytics system include: Industry work. Cognitive computing in conjunction with big data and algorithms that comprehend customer needs, can be a major advantage in economic decision making. The powers of cognitive computing and artificial intelligence hold the potential to affect almost every task that humans are capable of performing. This can negatively affect employment for humans, as there would be no such need for human labor anymore. It would also increase the inequality of wealth; the people at the head of the cognitive computing industry would grow significantly richer , while workers without ongoing, reliable employment would become less well off. The more industries start to utilize cognitive computing, the more difficult it will be for humans to compete. Increased use of the technology will also increase the amount of work that AI-driven robots and machines can perform. Only extraordinarily talented, capable and motivated humans would be able to keep up with the machines. The influence of competitive individuals in conjunction with AI/CC with has the potential to change the course of humankind.