Cognitive Computing represents a class of technologies that uses natural language processing and machine learning to enable people and machines to interact more naturally. It mimics human intelligence and computational capabilities such as understanding, reasoning, learning, and problem solving. In essence, it’s all about creating a computerized model that simulates the human thought process.


Imagine you have a super smart friend who always learns from new experiences, understands your language, helps you solve problems by thinking through them and even understand how you’re feeling. This is what Cognitive Computing does. It’s like a best pal who’s helping you to do things in a way that’s easy for you to understand.

In-depth explanation

Cognitive Computing is a sophisticated technology that aims to simulate human thought processes with the aid of self-learning algorithms that utilize data mining, pattern recognition and natural language processing. It focuses on replicating human intelligence by creating a cognitive system which can solve complex problems.

The goal of Cognitive Computing is to create automated IT systems that are capable of solving problems without human assistance. It combines Artificial Intelligence (AI), Neural Networks, Machine Learning (ML), Natural Language Processing (NLP), Sentiment Analysis and Contextual Awareness to solve day-to-day problems just like humans.

The core principles of Cognitive Computing consist of understanding, reasoning, learning, and interacting. The cognitive system understands the natural language along with the humans’ style of communication. It even has the ability to reason from the provided data and learns from the experiences to produce predicted outputs. Finally, it interacts with humans in their natural formats such as natural language and helps them make decisions based on evidence.

An example of Cognitive Computing in action is IBM’s Watson. Watson uses cognitive computing to process information more like a human than a computer. It can understand natural language, generate hypotheses based on evidences, and learn as it goes along.

Cognitive Computing systems can make sense of unstructured data (e.g., natural language, videos, images) which traditional systems had difficulty with. They can also learn and adapt from their past experiences, handle complex situations and make decisions based on their understanding. As such, these systems provide a significant leap in the field of automated problem solving.

Artificial Intelligence, Neural Networks, Machine Learning (ML),, Natural Language Processing (NLP),, Context Aware Computing, Data Mining, Sentiment Analysis.