Artificial Intelligence Vs. Cognitive Computing: How they Differ

Difference between Artificial Intelligence (AI) and Cognitive computing is quite an important question in the minds of people who are working in the business sector? In our daily lives, both of them have a great place but we aren’t aware that in actual terms what they want to explain. This question actually clears our response towards the upcoming and existing products that claim to do one or the other. If you are not aware of the difference between a platform powered by AI and the one which is associated with cognitive computing, and what are the implications of those differences, It will be very difficult for you to decide that what is best for your business or your application? First, lets read about the basic concepts related to them. 

Artificial intelligence: Letting computers do intelligent things.

The actions which are the most appropriate to take, and when they should be taken is decided by Artificial Intelligence agents. These form taken by these agents is mostly of a machine learning algorithms, neural networks, statistical analysis and more. A number of times AI information is fed actually over a long period of time so that it can “learn” the variables it should actually pay attention to and the desired outcomes could be there that is it provides a  perfect solution.

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The possible applications for AI are quite extensive and already are fully included into our daily routines, from the Siri/Alexa/Google voice assistant, to Netflix making recommendations based on the pattern of your viewing. AI and fully autonomous vehicles are inseparable if we talk about this in terms of the future, The AI watches countless hours of driving footage in training and is given some variables to look out for lanes, other cars, pedestrians and then provide a result based on its decision-making process.

Cognitive computing helps to solve problems with a human-like approach.

Cognitive computing is mostly classified as a simply marketing jargon, so getting a working definition is significant, though it’s more fluid right now, and there is not one accord that industry experts have implied to. Still, the bases for it is that cognitive computing systems actually intend to simulate human thought processes.

A number of same fundamentals as of AI are included in this process. They are machine learning, neural networks, natural language processing (NLP), contextual awareness and sentiment analysis, to pursue the processes of problem-solving that humans practice day in and day out. The result of cognitive computing defined by IBM is a “systems that learn at scale, reason with purpose and interact with humans naturally.”

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One emerging cognitive computing task is Sentiment Analysis which is done in order to fully know the context and nuances of human language as it must practice words on their deepest linguistic meanings. But, if we consider IBM and Watson, it actually makes clear to talk about medicine,  a doctor who inputs data about their patients, and cognitive computing algorithms analyze it by making use of mimicked human problem-solving. Some suggestions are then given by the application and even information is provided to assist the doctor to decide what to do next.

Are cognitive computing and AI the same kind of thing?

Both the terms are quite close but there are some fundamental differences in it.

• First thing is that human thought processes are not mimicked by Artificial Intelligence. Instead, a good AI system is the effortlessly the best probable algorithms for finding a solution to a given problem in the case of an autonomous car, evading collisions and staying on route. The data is not processed by it the same way as the human brain as it does not even try doing it. It is actually a far more complex and a system which is more fault-prone. And, an autonomous car is not the one who is just giving suggestions to the human driver. It is actually the one who is doing the core of driving.
• And second, cognitive computing actually supplements the own decision-making rather than making the decision for owners. In the field of medicine, a true AI would actually be taking all the decisions about how the patient is to be treated, essentially cutting the doctor out of the frame. The reason which makes cognitive computing important is just that there is true evidence which state that machine learning can supplement human medical diagnoses, but no one would claim that AI should actually take care of all the medical decisions right now.

What does the future hold for these two?

In the world which could be regarded as an ideal one, it is possible that proponents of AI and cognitive computing would actually be able to work together, especially in the coming period as the potential for these technologies strives to become more clear. To the AI and cognitive computing improvements, will only be a part when there would be improvements to the technologies, such as machine learning, natural language processing, handling big archives of unstructured data, and a lot more. So, there is a vested interest in less in-fighting and more focus on generating new ideas for pushing machine thinking more forward.

Think of a period when AI and cognitive computing are working in a proper sync with one another within a single system, operating from the same sets of data and the same real-time variables from the world around it. That is actually a self-ruling car that not only takes you to the ideal destination but also clear the prospect of why it is required to go there. Or, that is an emergency room that can right away triage you on the basis of your physical condition and your mental state of mind, and then giving out recommendations to the professionals, giving nurses and doctors a lot of time to get to work making you a better one.

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