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We're only on the cusp of it but if you're not yet thinking in cognitive terms, now's the time to start.
March 22, 2017
Cognitive computing is a term you're bound to be hearing more and more often.
Here's what it means — and how it overlaps with fields like big data, Internet of Things and machine learning.
There's no official definition of cognitive computing.
But when most people use the term, they have in mind applications or services that can engage with human thoughts — hence the descriptor cognitive — in a natural, automated way.
In a sense, computers have been doing cognitive computing for years.
An interface that is designed to adapt intuitively to the expectations of its human users, or a feature in your email that reminds you to include an attachment with a message when it thinks you intend to, are examples of cognitive computing features.
But in recent years, cognitive computing has assumed new urgency.
It has been driven by several disruptive trends within the IT world:
Big data. Large amounts of data — and analytics tools to process it — help applications understand and predict how humans think. In this way, the big data revolution allows cognitive apps to gain deeper, more accurate insight into human thought.
Internet of Things. The growth of the Internet of Things, or IoT, has increased demand for software that can engage naturally with your thought patterns. Today, cognitive computing is not just about how you interact with a PC. It involves anticipating everything about your lifestyle and day-to-day habits, from what time to turn on your furnace to which movies to suggest you watch.
Open data. Increasingly, information is open — meaning it's freely available to anyone who wants to harvest it and analyze it. This also creates new opportunities for building cognitive computing apps that draw on the vast quantities of open data available today — from medical research databases to Tweets to open source software source code.
These trends are feeding a rapid expansion of the world of cognitive computing.
IBM has made probably the biggest name in the cognitive computing field to date through platforms like Watson.
But most organizations that use machine learning or artificial intelligence are also engaged in the cognitive learning world — whether they realize it or not.
That means that there's a good chance your clients — or maybe even you — have a stake in cognitive learning applications and services.
Previously, you may have thought of cognitive computing features as a nice-to-have asset, rather than an essential one. Going forward, expect that to change. Device and service users will no longer expect to have to tell providers what they want. They'll expect the providers to know, and deliver, before they're asked.
That's the age cognitive computing is ushering in. We're only on the cusp of it now, but if you're not yet thinking in cognitive terms (OK, that's a bad joke), now's the time to start.
Christopher Tozzi started covering the channel for The VAR Guy on a freelance basis in 2008, with an emphasis on open source, Linux, virtualization, SDN, containers, data storage and related topics. He also teaches history at a major university in Washington, D.C. He occasionally combines these interests by writing about the history of software. His book on this topic, “For Fun and Profit: A History of the Free and Open Source Software Revolution,” is forthcoming with MIT Press.
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