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The term "cognitive computing" refers to systems that learn at scale, reason with purpose, and interact with humans naturally. These systems are designed to mimic the human brain's functioning by learning and interpreting patterns through data analysis. Cognitive computing involves self-learning systems that use data mining, pattern recognition, and natural language processing to mimic the way the human brain works. It is often used in fields such as Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning. Cognitive computing systems are not programmed in the traditional sense; instead, they are trained using large amounts of data and algorithms that allow them to learn how to perform tasks. These systems can process information in a more human-like way, understanding and learning from the context and interactions. They can also adapt to new information and generate insights from it.

The goal of cognitive computing is to create automated IT systems that are capable of solving problems without human intervention. This technology is used in various applications, such as voice recognition, sentiment analysis, fraud detection, risk assessment, and customer support.

Cognitive computing is a key component of IBM's Watson, a technology platform that uses natural language processing and machine learning to reveal insights from large amounts of unstructured data. Watson can understand the nuances of human language, sift through vast amounts of data, and provide evidence-based responses to its user's questions.

In conclusion, cognitive computing represents a significant shift in the field of information technology. It is a step towards creating machines that can interact with humans in a more natural and intuitive way, understand complex problems, and make decisions based on a deep understanding of the context. Cognitive computing is not just about automating tasks but also about enhancing human capabilities. It can help humans make better decisions, solve complex problems, and even predict future trends. This technology is still in its early stages, but it has the potential to revolutionize various industries, from healthcare to finance, by providing more accurate, personalized, and efficient services.