Human thinking is beyond imagination. Can a computer develop such ability to think and reason without human intervention? This is something programming experts at IBM Watson are trying to achieve. Their goal is to simulate human thought process in a computerized model. The result is cognitive computing – a combination of cognitive science and computer science. Cognitive computing models provide a realistic roadmap to achieve artificial intelligence.

Cognitive Computing (COC) aims to build highly cognitive machines with low computational resources that respond in real-time. However, scholarly literature shows varying research areas and various interpretations of COC. This calls for a cohesive architecture that delineates the nature of COC. We argue that if Herbert Simon considered the design science is the science of artificial, cognitive systems are the products of cognitive science or 'the newest science of the artificial'. Therefore, building a conceptual basis for COC is an essential step into prospective cognitive computing-based systems. This paper proposes an architecture of COC through analyzing the literature on COC using a myriad of statistical analysis methods. Then, we compare the statistical analysis results with previous qualitative analysis results to confirm our findings. The study also comprehensively surveys the recent research on COC to identify the state of the art and connect the advances in varied research disciplines in COC. The study found that there are three underlaying computing paradigms, Von-Neuman, Neuromorphic Engineering and Quantum Computing, that comprehensively complement the structure of cognitive computation. The research discuss possible applications and open research directions under the COC umbrella.

Machine learning, artificial intelligence, natural language processing, deep learning, robotics, and several other technologies have enabled businesses to leverage human intelligence and evaluate inputs for maximum accuracy and precision. For example, you now have image recognition software that acts as a scanner and finds the best search options on Google after interpreting what the image is. So, the application is based on ML, natural language processing, and artificial intelligence. It imitates a human who uses the item or object through the eyes and interprets the results in mind. Although all these disruptive technologies are individually the best in their field, combining them, it's a challenge.

Nothing can beat human thinking in any way. Most programming experts are on the verge to create such a computer system that can think and reason without any human intervention. Basically, they are working on cognitive artificial intelligence that can process human thought into a computerized model. A cognitive computer is a system that learns at scale, reasons with purpose, and interacts like humans on a natural basis. Instead of being programmed, these systems work through learning and reasoning from their interactions with human beings.

The human brain is nothing short of a marvel. We are reminded of this fact each time we read about a technology helping it out of boredom or drawing inspiration from it. How often have you heard complaints about the fact that creativity is being sucked out of human minds when they must do monotonous tasks? Well, Artificial intelligence (AI) and cognitive computing are two stellar technologies crafted in order to reduce human intervention and improve business processes across industries. You needn't be confused about the interchangeable usage, because certain features set AI and cognitive computing apart from each other.

Cognitive computing has been on a lot of minds lately. Looking into the capabilities of Artificial Intelligence to imitate human perception to some extent, the technology innovators have discovered that cognitive computing is a better fit for that. We suddenly realized that a lot more can be done in that regard -- instead of imitating only the perception, we can have technology make decisions like humans. Sharing the idea among the team members of AIHunters, we have tasked ourselves with an ambition of cognitive business automation in the media and entertainment industry. Let us take you on a tour of how we did that -- deliver the solution that puts innovation towards optimizing the video processing and post-production, while pushing beyond the limitations of regular AI analysis.

The main goal of cognitive computing is to simulate human thought processes in a computerized model. Using self-learning algorithms that use data mining, pattern recognition, and natural language processing, the computer can mimic the way the human brain works. Furthermore, While computing in Six Industries Inc has been faster at calculations and processing than humans for decades, they haven't been able to accomplish tasks that humans take for granted as simple, like understanding natural language. According to IBM, Watson could eventually be applied in a healthcare setting to help collate the span of knowledge around a condition, including patient history. Furthermore, Journal articles, best practices, and Encryption labs analyze that vast quantity of information and provide a recommendation.

Artificial Intelligence and Cognitive Computing are often used as interchangeable terms, and as much as both refer to machines with human-like capabilities, there are some big and important differences. AI is talked about abundantly, and equally abundant are the definitions with which we want to describe this discipline. In synthetic terms, it could be said that with AI we try to make computers able to do things that the human mind can do. Some of these, such as more or less sophisticated forms of reasoning, are normally considered as belonging to the field of intelligence, while others, for example computer vision, are not in the strict sense of the word. In each case there is the involvement of psychological skills, such as perception, association, prediction, planning, motion control, which allow humans and animals to achieve their goals, whatever they are. Among the many possible definitions of Cognitive Computing, one is particularly emblematic, if only for its generality that brings little in the way of information content: the use of computer models to simulate human mental processes in complex situations where responses may be ambiguous or uncertain.

Artificial intelligence (AI) and cognitive computing can work together closely by connecting technology with the physical world. The concepts of AI and cognitive computing are deployed widely in various sectors. AI and cognitive computing can self-learn and adapt to new surroundings. However, there is a slight difference between these two technologies. AI creates devices that can act smarter than humans, whereas cognitive computing creates devices that adapt to the surroundings and communicate with humans naturally.

OTT platforms are now the primary entertainment source for a lot of people. You want to watch a movie, catch up on your favorite TV show, or just kick back and support your sports team -- you can access any content more conveniently via streaming services. There is a ton of effort that goes into keeping all of those users engaged with the OTT platform. Apart from delivering the best content, the platforms have to think about ways to make the viewing experience the most convenient. So, let's talk about just that -- you can enhance user engagement by providing a better viewing experience with cognitive computing. Ever find yourself looking at the credits when the movie or a TV series episode is over?