July 24, 2017 | Written by: Andy Thurai
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In 2017, digital disruption is history. If you are not thinking about cognitive disruption, your business is way behind the technology curve.
In the recent IBM annual survey of global CEOs, about 73 percent say cognitive computing will play an important role in the near future of their organizations, with the same sentiment echoed by other top executives as well. While almost three-fourths of CEOs agree that their businesses, and their industries, will be disrupted by cognitive computing in the near future, surprisingly only about half of these CEOs are planning to adopt cognitive computing by 2019.
While that may seem stunning, the primary reason is pretty clear: infusing cognition into an existing infrastructure is extremely difficult.
As an example, the cognitive brain known as IBM Watson took decades to build, cost hundreds of millions of dollars and involved thousands of super-bright engineers. Given the substantial investment required to build cognitive apps, the average enterprise may not have the tolerance or the capital to expend resources at that level. Therefore, it’s critical to look for a cloud platform that not only brings a robust, scalable, and secure environment, but also comes with cognitive capabilities already infused at the core of the platform.
Let’s take a step back and ask, “What is cognitive computing?” It is an effort to mimic the human brain’s learning process, thought process, reasoning, analysis, and decision making. At times people get confused this with machine learning (ML), business intelligence (BI), deep learning (DL) and other existing analytical solutions.
A major difference between existing systems and cognitive systems is that cognitive systems can understand what’s called “dark data.” Dark data, also known as unstructured data, cannot be analyzed by existing systems to get insights that can help with the decision making.
Dark data is growing exponentially, as it is estimated to be about 80 percent of world’s current data collection. It’s estimated to grow to about 90 percent by 2020. This noisy, mostly machine-unreadable data comes from unstructured data groups such as images, telematics, sensor information, video, audio and so on.
The other difference is that cognitive systems can help users move away from the “programmable era” and into the “cognitive era.” Historically, computers needed to be programmed explicitly on what to recognize and how to react to different scenarios. However, these traditional, non-cognitive systems hit a brick wall when they encounter a scenario that they are not programmed for.
In contrast, cognitive systems have critical thinking capability, much like a human brain. When presented with a new scenario, they can learn, understand, analyze the situation and act without the need for additional programming to make authoritative decisions.
Ultimately, cognitive computing is not about mankind against the machines, as Terminator movie series would suggest. It is about machines collaborating with mankind, augment the human brain, man and the machine turning into one, with specific goal in mind. It is about the machines helping mankind. Now is the time to work together to build smarter cognitive solutions and apps for your enterprise using IBM Watson Cloud Platform.
In my next post, I’ll discuss how Watson can help organizations achieve their goals.
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