Insights and Inspiration


Cognitive Computing: Future of Artificial Intelligence

Cognitive Computing: Future of Artificial Intelligence

Monika Kumar | Engineer at Webio

Long before it started, 2017 was being heralded as the year of AI. Each news article and post talking about automation, healthcare research and digital assistants only increased the expectation of what AI could deliver. But throughout all these discussions, one critical fact was overlooked, and has remained overshadowed in all the zeal for social transformation ascribed to cognitive computing's prowess. Prakash Nanduri CEO of Paxata stated that "people in the industry say that if they can do cognitive computing, they can solve cancer". But, the key lies in transforming the data into relevant information.

Cognitive Computing: The Essence

Cognitive Computing, Artificial Intelligence and Machine Learning are the three buzz words of today's IT era. From smart homes, to self-driving cars, to digital assistants, we have seen that machines can speak, hear, write, read and learn but the main question is can they understand? Can they make their own decision? Can they respond without being pre-programmed?

Cognitive means "to think" and "computing" is processing using computers. Cognitive computing is making computers smart enough to think like humans. Cognitive computing is not one single technology, but it is a group of powerful technologies like artificial intelligence (AI), machine learning (ML) and natural language processing. It uses AI and ML to generate powerful systems which can sense, learn and respond. It plays a critical role in advancing and automating the core tenets of data management such as data modeling, data quality, data transformation and integration to ignite the applications and analytics required for the data. Researchers are claiming that Cognitive Computing is more powerful than Artificial Intelligence as it is basically designed to solve problems like human beings do.

IBM defines Cognitive Computing as "systems that learn at scale, reason with purpose and interact with humans naturally."

It is not only replicating human brains but is also trying to create a system that handles huge amounts of data because human brains can't remember humongous data. In the last 2 years, 90% of the data which is present in the world today has been created and most of this data is unstructured. Just think about that.

So here is where Cognitive computing comes in. It is basically designed to handle huge amounts of unstructured data and is useful in any field where massive amount of complex data needs to be analyzed and processed for example in finance, retail, education, supply chain, manufacturing, healthcare, aviation etc.  But to understand unstructured data, we need more intelligent and smart systems and Cognitive Computing is one such effort.

AI and Cognitive Computing Are Not One and the Same

People often get confused between AI and cognitive computing. The personal digital assistant which we use in our day to day lives such as such as Amazon's Alexa, Apple's Siri, Google Assistant, these are not cognitive systems. They all have pre-programmed set of instructions or responses and they only respond to limited number of requests. But Cognitive computing make systems smart enough to think and respond without pre-programmed sets of instructions.

Artificial Intelligence (AI) is making computers smart and do intelligent things. The roots of AI are machine learning algorithms, statistical data analysis, deep learning neural network and many more. In AI a model has been provided with long periods of historical data so that learning can be facilitated from the input and output variables and provide a solution.

AI uses machine learning algorithms that learn from historical data and make predictions.  It can also decide what actions to take and when. As compared to traditional programming where programmers use to write sets of rules or instructions, in AI the algorithm trained itself by finding out patterns in large volume of historical data. Deep learning neural networks are much more stronger and smarter than machine learning as they have layers where the output of one layer is input to another.

E.g. Amazon recommendation system, Google voice assistant, Apple Siri, chatbots

One step ahead of Artificial Intelligence, Cognitive Computing includes artificial intelligence, machine learning and natural language processing. These systems are self-learners, after giving initial instructions they start learning on their own, based on the data they receive. It is making computers think like human beings coupled with high computational power and memory.

The Goal of Cognitive Computing

The main goal of Cognitive systems is to aid humans without their assistance, for example, in a call centre where customer service representatives are getting assistance from Cognitive systems to improve how they engaged, respond and deliver better customer experiences.  

The ability of Cognitive Computing to absorb different characteristics of data and to comprehend, analyse and learn from it has the potential to unveil novel insights. These potential solutions can play an indispensable role in many different areas especially in life science and medical healthcare which are in dire need of accelerated and radical innovations.

As we enter a time when computers are better able to think like humans, they will enable us to do things better and expand our horizons. Life as we know it is forever changed. 

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