Cognitive computing systems may play the role of an assistant or a coach for the user, and they may act virtually autonomously in many problem-solving situations. Their output may be prescriptive, suggestive, instructive, or simply entertaining.
For example, your personal assistant, should it be Siri, Google Assistant, Alexa or Cortana is a great example of a Cognitive computing system for personal use.
But can Cognitive Computing capabilities be used in enterprise system? Of course it can and there are multiple examples: fraud detection in finance, investment risk management, commerce recommender systems, predictive maintenance in manufacturing, detection of anomalies in oil and gas production cycle to prevent oil spills and so on.
Cognitive computing refers to cognitive intelligence. Basically, one teaches a robot to do what all people do, with zero mistakes. The problems that need to be solved are various.
In order to achieve the cognitive level of computing, the systems must be adaptive, interactive, iterative and contextual.
Adaptive – as the information changes, and goals and requirements evolve, the systems must learn. They must be engineered to feed on dynamic data in real time, or near real time.
Interactive – the systems must easily interact with users so that those users can define their needs in a comfortable and natural way.
Iterative – the systems must aid in defining a problem by asking questions or finding an additional source input if a problem statement is ambiguous or incomplete.
Contextual – the systems must understand, identify, and extract contextual elements such as meaning, syntax, time, location, appropriate domain, regulations, user’s profile, process, task, and goal.
This is the problem that the solutions on the market today are facing. Take IBM`s Watson for example. Watson can, according to its makers, understand all data and interact naturally with people. The main question is how mature this software is, that is, at what age level can it perform?
Compared to our solutions in VCA AG, Watson is at the level of a four year old child. Our software solutions are the answer for all the problems listed above. Our systems learn and feed on information in real time. The solutions we offer may also interact with other processors, devices and Cloud services. They draw on multiple sources of information, including both structured and unstructured digital information. They also address another important requirement of having the most important data available for the real-time ad-hoc access while being able to reach a long track of historical data for better insight.