Watson Not Only Smart Machine In Town - InformationWeek

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Data Management // Software Platforms

Watson Not Only Smart Machine In Town

Up-and-coming vendors in the genre include AlchemyAPI, Digital Reasoning, Highspot, Lumiata, and Narrative Science, Gartner says.

8 Gadgets For The High-Tech Home
8 Gadgets For The High-Tech Home
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So what's a smart machine? As a computing model designed to analyze growing volumes of unstructured data, including video, images, and human language, a smart machine, or cognitive computing system, uses artificial intelligence and machine learning algorithms to "sense, predict, infer and, in some ways, think," according to IBM.

In a recent report, "Cool Vendors in Smart Machines, 2014," Gartner named three well known examples of smart machines, including IBM's Watson, Google Now, and Apple's Siri, and predicted the technology will gain wider acceptance this decade. It also spotlighted a few up-and-coming vendors in the genre, including AlchemyAPI, Digital Reasoning, Highspot, Lumiata, and Narrative Science.

Digital Reasoning's Synthesys platform, for instance, is a machine-learning system designed to quickly analyze massive volumes of digital communications, including email, chat, voice, and social media. It can uncover relationships and facts about people, places, and things, the company claims, and reveal potential security, risk, and compliance issues, among other problems.

[Want to capitalize on all that data you're generating? Step one: Bury the hatchet. See Big Data Forces IT & Business To Get In Sync.]

Today's primary users of smart machines are the intelligence and financial services communities, according to Marten den Haring, senior VP of products for Nashville-based Digital Reasoning.

"Much of our history is building an expertise in understanding human language data, and applying that to some really interesting and important problems, starting with the intelligence community and moving into financial services," said den Haring in a phone interview with InformationWeek.

Intelligence agencies, for instance, need to query unstructured data from a variety of sources. Questions may include: "Who's talking to whom about what, who's traveling to what location, what are the networks we know of, and how can we discover networks we don't know?"

In the financial services industry, "there are real problems tied to operational and reputational risk, such as not being able to properly analyze and understand what people are talking about in emails or chats," he added.

Digital Reasoning's Synthesys platform.
Digital Reasoning's Synthesys platform.

Digital Reasoning is targeting the healthcare market as well. In addition to conventional uses -- fraud detection, risk and cost reduction, and regulatory compliance -- machine-learning platforms show potential in other areas as well.

"There's a strong desire to start looking at more positive outcomes from this technology, whether it's in better customer service and patient care, or finding and correlating interesting things that can give you an edge in a competitive landscape," said den Haring.

Of course, buzzwords like "smart machines," "big data," and the "Internet of Things" are often overused by marketers. But den Haring said the terms can help describe the explosive growth of digital machines and the information they generate.

"They're just a way for us to say we have amazing growth and a variety of data we didn't have before. And with the Internet of Things, that's only going to become more of an issue.

"Cognitive computing is interesting because it really speaks to the core underlying issue that is at play here: Humans are creating so much data. They have created a lot of machines that are creating even more data -- and now they need help to deal with all of this data."

One of Digital Reasoning's long-term goals is to put smart-machine technology in the hands of individuals, not just large enterprises with deep pockets.

"Someday all software will learn, and that day is nearly upon us," said Tim Estes, CEO and founder of Digital Reasoning, in a statement.

However, it remains unclear how cognitive computing will evolve and gain greater acceptance in mainstream business- and consumer-focused applications.

Could the growing movement toward open-source hardware rewrite the rules for computer and networking hardware the way Linux, Apache, and Android have for software? Also in the Open Source Hardware issue of InformationWeek: Mark Hurd explains his "once-in-a-career opportunity" at Oracle.

Jeff Bertolucci is a technology journalist in Los Angeles who writes mostly for Kiplinger's Personal Finance, The Saturday Evening Post, and InformationWeek. View Full Bio

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User Rank: Author
4/21/2014 | 1:05:40 PM
Smart machines
Social sentiment analysis is helping mine social chat for customer service issues, but it will be interesting to see what smart machine technologies can do with identifying customer service issues better and faster. The financial and healthcare examples cited make sense. What would others be?
Charlie Babcock
Charlie Babcock,
User Rank: Author
4/21/2014 | 3:31:36 PM
Credit card fraud detection is also a "smart" system
The fraud detection systems, such as Fair Isaac's, used by credit card companies are learning systems that are good at what they do. Otherwise, credit card fraud would be out of control.
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