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  • Writer's pictureLaila Alahaideb

Cognitive Computing

Cognitive Computing is a branch of computer science widely related to the Artificial Intelligence (AI) concept and refers to a range of technologies, including machine self-learning, human-computer interaction(HCI), Natural Language Processing (NLP), data mining, and others, that are founded on the scientific theories behind AI and signal processing.

Its goal is to resolve complex issues that are unknown and ambiguous or issues that can only be resolved through human cognitive reasoning. In general, technology platforms that are built on the fields of AI and signal processing are referred to as Cognitive Computing. These platforms include, among other things, technology for Machine learning, Dialog, NLP, Object Recognition, HCI, Big data, IoT, Probabilistic reasoning, Computer vision, and Narrative generation. As a result, putting these three ideas; Generation of hypotheses, Continual learning, and Deep contextual insight into practice makes a system cognitive.

Additionally, cognitive computing makes it possible to gather and process enormous amounts of data of all kinds, analyze and understand it, and gain insights to suggest the best course of action. So, it’s the use of computerized models to simulate the human thought process in complex situations. On the other hand, The IBM firm established the "cognitive enterprise" (CE) idea, which posits, among other things, the cognitive technologies used to improve enterprise intelligence.

Increased use of cognitive technologies, including AI, advanced analytics, high-performance computing, and cyber-physical systems, in particular, enables businesses to create new value through improved situational awareness, operational excellence, and increased reactivity and resilience.


Computer vision, an interdisciplinary branch of science, is the study of how computers can derive deep knowledge from digital images or videos.

Continual learning is the ability of a model to learn continually from a stream of data.

HCI is the study of the interaction between people, computers, and tasks.

Hypothesis generation is an educated “guess” of various factors that are impacting the business problem that needs to be solved using machine learning.

Narrative generation refers to the task of constructing computational models of the way in which humans build stories.

NLP is a branch of linguistics, computer science, and artificial intelligence studies how computers and human language interact, focusing on how to design computers to process and examine massive volumes of natural language data.

Probabilistic reasoning is the concept of probability to denote the degree of knowing uncertainty as a method of knowledge representation. To deal with uncertainty, probabilistic reasoning combines logic and probability theory.

Related Knownlagment:

O. Pilipczuk, “Cognitive Computing—Will It Be the Future ‘Smart Power’ for the Energy Enterprises?,” Energ. 19961073, vol. 15, no. 17, p. 6216, Sep. 2022, doi: 10.3390/en15176216.

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