| Cognitive computing is the use of computerized models to simulate the human thought process in complex situations where the answers may be ambiguous and uncertain. The phrase is closely associated with IBM's cognitive computer system, Watson. Cognitive computing overlaps with AI and involves many of the same underlying technologies, including expert systems, neural networks, robotics and virtual reality (VR). How cognitive computing works Cognitive computing systems can synthesize data from various information sources, while weighing context and conflicting evidence to suggest the best possible answers. To achieve this, cognitive systems include self-learning technologies that use data mining, pattern recognition and natural language processing (NLP) to mimic the way the human brain works. Using computer systems to solve the types of problems that humans are typically tasked with requires vast amounts of structured and unstructured data, fed to machine learning algorithms. Over time, cognitive systems are able to refine the way they identify patterns and the way they process data to become capable of anticipating new problems and model possible solutions. To achieve those capabilities, cognitive computing systems must have five key attributes, as listed by the Cognitive Computing Consortium. Adaptive: Cognitive systems must be flexible enough to learn as information changes and as goals evolve. The systems must be able to digest dynamic data in real time and make adjustments as the data and environment change. Interactive: Human-computer interaction (HCI) is a critical component in cognitive systems. Users must be able to interact with cognitive machines and define their needs as those needs change. The technologies must also be able to interact with other processors, devices and cloud platforms. Iterative and stateful: Cognitive computing technologies can also identify problems by asking questions or pulling in additional data if a stated problem is vague or incomplete. The systems do this by maintaining information about similar situations that have previously occurred. Contextual: Understanding context is critical in thought processes, and so cognitive systems must also understand, identify and mine contextual data, such as syntax, time, location, domain, requirements, a specific user's profile, tasks or goals. They may draw on multiple sources of information, including structured and unstructured data and visual, auditory or sensor data. | 
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