The hype and the level of interest surrounding it are new and behind the hype lies a potential for increased productivity and the problem-solving ability that is too complex for average human beings and improved knowledge-based transactions and consumer interactions. The processes behind cognitive computing use the same principles like AI, which includes machine learning, contextual awareness, sentimental analysis and natural language processing.
Cognitive computing has the ability of computers to replicate human thought process and is different from AI in various ways. The latter does not mimic human thought processes and solves the problem using the best-known algorithm present. Falsely mistaken for having the capability to “make” decisions for humans, cognitive computing on the contrary, is responsible for supplementing or complementing with our cognitive abilities of decision making. The use of cognitive computing in various industries is rising, but the technology is still in its research phase on its proper implementation in the various fields for its appropriate use.
The deployment of cognitive computing requires following a certain set of rules to achieve the desired goals. Determining the scale of the implementation and then automating the process towards achieving the scale necessary is essential. The next level of deployment includes the creation of Application Programming Interfaces (APIs). The stage of automation middleware provides 75 percent of the entire share that goes in achieving the solution. Application programs are also created to follow the progress of different domains. Once cognitive applications are deployed, there is a need to monitor for possible updates. With the concept gaining popularity, it is expected that it will develop and be implemented in various industries.
