The accumulation of ever-expanding structured and unstructured data led to the third age of computing; Cognitive Era. Cognitive computing can make sense of that data by learning and reasoning from their interactions with us instead of being explicitly programmed. This makes it scalable with the volume, complexity and unpredictability of information and systems in the modern world.

Cognitive systems are not trying to replicate human brains, but rather inspired by human intelligence to understand the complex systems. This rises up different kinds of challenges and opportunities in every industry. The success of such systems is measured by its usefulness like return on investment, new market opportunities, cured diseases, utilized energies and saving lives.

The history of computing

Let me take you back to 1900s: the Tabulating Era was made up of mechanical systems that can perform simple tasks as calculation. In 1950, the Tabulating Era has ended and the Programmable Era has just started. It was a shift from mechanical tabulators to electronic systems with a huge improvement in storage and performance capabilities. Any computing device we know beginning from the mainframe until the personal computer and smartphone is a programmable computer.

IBM has played a central role in the development of the previous two eras of computing, the Tabulating Era and the Programming Era. Similarly, in 2011, IBM made an evolution in the Cognitive Era by introducing the world’s first cognitive system, Watson, which defeated Ken Jennings and Brad Rutter at Jeopardy!.
Computing Eras

Applications of Cognitive Computing

Watson is known as the first platform with this cognitive capabilities for all industries. When Watson wins at Jeopardy, the Question & Answering system inside Watson was moved to the cloud in order to scale. Then, IBM build a suite of Watson services beside Watson Q&A, and offer it as a service.

IBM Code has many journeys where cognitive is applied in various industries including but not limited to tourism, banking and transportation.


There is a dramatic increase in the number of mobile applications that improves the digital experience for the traveler. This journey shows an example where cognitive services such as Watson Conversation is used to enhance the traveler experience. The application provides a personalized recommendation for restaurants, hotels, or cityscape.


Chatbot become an essential asset for many organizations, to provide support for customers instantly. Having a chatbot which is programmed to answer customer question saves a lot of money, and a lot of time. Although the journey of cognitive in banking is built as a fictional financial institution, it demonstrates the chatbot capability to rapidly look through FAQ documents to correctly choose the best responses for the customer using Watson Discovery. Another cognitive service, Watson Tone Analyzer, is used in this application to detect emotional tone of the customer from his input.


As mentioned above, cognitive computing is about dealing with exponentially growing data. Analyzing that data can give an insight to diagnose or solve problems, Traffic as an example. The journey of analyzing traffic data is demonstrating how to use Jupyter Notebooks in IBM Data Science Experience (DSX) to load, visualize, and analyze data. Further, the journey explores PixieApps to create a dashboard, and Mapbox GL to create an interactive map.

At the end, every industry now is swamped in data which open boundless opportunities for cognitive computing applications to access and get insights from that data. You can read more about cognitive computing in one of IBM White Papers titled Computing, cognition and the future of knowing and if you are interested, look into Compilation of Watson AI Use Cases.

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