Cognitive Computing Powers 6 Smart Deployments - InformationWeek

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Data Management // Big Data Analytics
11:06 AM
Lisa Morgan
Lisa Morgan
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Cognitive Computing Powers 6 Smart Deployments

Cognitive computing, which enabled IBM Watson to win Jeopardy!, is helping professionals get expert assistance and make faster, more intelligent decisions based on highly complex big data.
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(Image: Geralt via Pixabay)

(Image: Geralt via Pixabay)

Cognitive computing is going to transform a lot of things. Among them, how humans and machines interact, how companies interface with their customers, and how cybersecurity threats are managed. In fact, its potential uses are practically limitless, although not everyone is approaching the problem in the same way. Regardless of which technologies innovators are using or planning to use, their common goal is to mimic human reasoning at machine-level scale and velocity.

Since IBM Watson won a Jeopardy! match on television in 2011, IBM commercialized its technology, expanded its set of APIs and launched a new consulting practice. In September 2015, the IBM Watson team announced it had more than 100 partners developing cognitive apps, products, and services going into market. However, IBM Watson is just one example of how companies are approaching cognitive computing.

More companies are using machine learning, artificial intelligence (AI), natural language processing (NLP), or some combination of those and other technologies to make better sense of the vast volume, variety, and velocity of big data.

Some of them are adding or plan to add more types of technology to the mix, such as contextual awareness, neural networks, more sophisticated pattern recognition, visual sensing, and other technologies that, when combined, enable machines to more accurately emulate human thought and reasoning. In short, cognitive computing is a superset of technologies that are being combined in different ways to solve both general and specific problems.

[Read IBM Cognitive Colloquium Spotlights Uncovering Dark Data.]

However, the reasoning capabilities, matching capabilities, learning capabilities, and language-processing capabilities that will enable organizations to uncover new levels of insights may well raise a new wave of privacy and security concerns along the way.

These technologies will likely fuel the debate about the balance between humans and machines as they gain momentum, whether regarding the fear of replacing more human decision-making with automated systems or the doomsday AI threat some perceive.

On the other hand, there is a limit to what humans can do in today's real-time economy, which is why the seeds of cognitive computing are already sprouting across industries such as healthcare, financial services, and event management.

Page through this slideshow to learn how some of the capabilities are being used today.

Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include ... View Full Bio

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User Rank: Apprentice
11/15/2015 | 9:06:18 AM
What about other usage of cognitive computing ?
What about the other usages of cognitive computing, especially on a non-marketing or non-business arena ? such as in the medical space ? in the education space, or even for cities organization ? There are hundreds of application that are already in use, and Watson is supporting some of them, but not all. 

The level of innovation and disruption that will become possible thanks to cognitive computing is only as its beginning
Li Tan
Li Tan,
User Rank: Ninja
11/7/2015 | 1:44:13 AM
Re: Oracle and cognitive computing
The core essence of big data lies in analytics part - what kind of conclusion you can draw from big data? How useful they are? Can you make wise decision based on the analytical result?
[email protected],
User Rank: Apprentice
11/6/2015 | 8:35:14 PM
Future jobs for humans
Thanks for this thoughtful look forward.  Cognitive computing is a common example of artificial intelligence as it includes categories such as natural language processing and machine learning. 

As such software is applied to more and more tasks previously executed by humans, questions naturally arise about our role in the workforce and economy of the future.  But rather than replace humans, machine learning and other AI applications actually will create the need for human contributions on new levels.  Machine learning applications, for example, are like talented but narrowly focused employees.  To success these applications need inventors, business managers, salespeople and technical support personnel.  Those are the new human jobs of the future.

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