Cognitive Computing, which is the simulation of the human thought process using AI technologies like Machine Learning, Deep learning, Neural networks, etc have expansive horizons. It aims to study the various characteristics of human cognitions like emotions, reasoning, perceptions, and memory. On the other hand, Artificial Intelligence (AI) concentrates on solving complex problems by augmenting human thinking. Thus the combination of Artificial Intelligence and Cognitive computing provides a deeper knowledge of human intelligence and behavior.
Nowadays we have human-controlled autonomous systems such as the Flight Management Systems(FMS) for pilots, that automates a variety of in-flight tasks thereby reducing the workload of the flight crew. We are now heading towards an increasing number of autonomous systems to reduce human activity, with the presumption that humans are not entirely predictable or reliable.
As AI is finding its relevance across various industries and professions, the role of cognitive computing becomes crucial. For any industry to be profitable, it needs to have deep knowledge as to what will work for the human brain and the ways to satisfy it. AI needs to be utilized to achieve these requirements in businesses. An understanding of the significance of cognitive computing in AI across various industries are:
- HR can reap the benefit of cognitive computing to improve the efficiency of its workforce and develop them. As far as HR is concerned, it’s all about interacting with employees and HR managers need to have an understanding of the mental and emotional process in their employees to bring the best out of them and increase their business value.
- Banking experts providing the automated financial services need to have an understanding of the human mind and how to engage their customers through the AI-driven services offered by them draws the significance of cognitive computing in AI.
- The engineering and medical tools and devices need to be prepared so that it adapts to the human brain needs and disentangle it for them. A typical example is that of the automated cars which need to be structured so that people can see how to function them.
Thus in the future, experts are to adopt cognitive computing to replicate intelligence in AI to understand humans better.
