Brands
Discover
Events
Newsletter
More

Follow Us

twitterfacebookinstagramyoutube
Youtstory

Brands

Resources

Stories

General

In-Depth

Announcement

Reports

News

Funding

Startup Sectors

Women in tech

Sportstech

Agritech

E-Commerce

Education

Lifestyle

Entertainment

Art & Culture

Travel & Leisure

Curtain Raiser

Wine and Food

YSTV

ADVERTISEMENT
Advertise with us
Disclaimer-mark
This is a user generated content for MyStory, a YourStory initiative to enable its community to contribute and have their voices heard. The views and writings here reflect that of the author and not of YourStory.

Move Over Robotic Process Automation, Cognitive Computing is Here

Cognitive Computing systems are gradually improving their ability to learn, adapt, calculate, and recommend solutions in real time.

Move Over Robotic Process Automation, Cognitive Computing is Here

Tuesday November 21, 2017 , 4 min Read

Cognitive Computing is the future of Process Automation

Cognitive Computing is the future of Process Automation

It is true that automation has always been able to solve problems and simplify processes that are seemingly complex to humans. However, today’s technology landscape is far more different from what it used to be in the yesteryears. It is getting more and more complex; due to the advent of cloud computing, smartphones, social networks, and a vast ecosystem of sensors. In fact, the complexity lies in processing the massive volumes of information produced by these innovations—we struggle to make sense of it.

Since time immemorial, several innovations in automation have been developed to make things simple for us. One such innovation is the Robotic Process Automation (RPA).

How does Robotic Process Automation help us?

Robotic Process Automation has been able to add a considerable amount of automation to business operations. Technically speaking, it uses rule-based automation to handle high amounts of data and repeatable tasks.

Innovative as it may seem, RPA has it’s own limitations. Ideally, RPA triggers macro level task automation; which simply means that it works on a pre-defined and finite set of rules or workflows. Practically, however, in the real world scenario, these so-called “finite set of rules” do not work effectively everywhere. RPA lacks the level of intelligence typically required to understand and explore new areas of business operations; and make informed decisions – on its own.

This is where cognitive computing comes in; evolving and gradually breaking the limitations of computing in all aspects.

What exactly is Cognitive Computing?

Cognitive Computing can be termed as the combination of cognitive science – study of the human brain – and computer science. Its primary goal is to simulate the human thought process in a computerized model; using self-learning algorithms that deploy data mining, pattern recognition, and natural language processing. In a nutshell, computers can mimic the way we think and work.

Although previously, computers have always been able to do faster calculations and processing than humans, their capabilities are devoid of understanding natural languages or recognizing objects in images. Today, cognitive computing can easily accomplish these things.

How capable is Cognitive Computing?

As we already know, cognitive computing systems are gradually improving their ability to learn, adapt, calculate, and recommend solutions in real time. They are able to understand the world better; just like we do, using their senses (or sensors). Moreover, they can respond to various situations—just like we do. In this manner, we humans will be able to trust their recommendations and rely on them for solving most of our real-world problems. This indeed is a huge leap forward into the future; mastered with a series of technological advancements. Over time, cognitive computing will have a greater impact on our personal lives, businesses, healthcare and more. 

What are the use cases in the real world scenarios?

Healthcare

For instance, in healthcare, cognitive computing can be implemented to help doctors accumulate a large quantity of information related to the patient’s condition. This includes patient history, best practices, the diagnostic tools and more. Analyzing these, cognitive systems will provide a precise recommendation that can be trusted by doctors. Consequently, the information will enable them to make better treatment decisions. As you can see, here, cognitive computing is focused on a single goal - enhance the doctor’s skills.

Businesses

Just like healthcare, cognitive technology also impacts businesses in many ways. For example, in today’s digital landscape, businesses need to be constantly in touch with their customers; no matter where they might be. Embedded with exceptional intelligence, cognitive computing can not only help businesses connect with their customers, but can also render high levels of speed and services. Technically, it analyzes unstructured data; listens to the words of customers and understands their actions. This helps the technology to remember their needs and preferences to better serve the businesses. Moreover, this process can be done with numerous customers multiple times, and simultaneously.

In a similar way, the technology can be effectively applied in other industrial realms.

What the Future Holds for Cognitive Computing

Cognitive Computing has emerged as an intriguing area; attracting tech-savvy professionals, and paving a path for numerous industrial applications. Indeed, the technology enablement brought about by digital transformation is gradually narrowing the gap between humans and computers—where we work together to produce better outcomes. 

The possibilities of cognitive computing are endless. Sophia, the humanoid robot, and the first one to become a Saudi Arabian citizen is a clear evidence that the technology is taking a whole new approach; something much more advanced, and beyond our imagination.