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IBM Watson CTO sees bright future for cognitive computing

25 Sep 2015  | Rick Merritt

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Rob High was still an unbeliever when it came to cognitive computing back in early 2012. Now he is its evangelist as the CTO for IBM's Watson initiative. High was an IBM fellow working in the field of service-oriented architecture when he was offered the job of CTO for Watson. "I turned it down twice," he noted.

He rejected the job because he wasn't familiar with the Watson team's field. From a distance, it didn't seem serious enough with an IBM Power system running Watson software acting as a contestant on the TV game show "Jeopardy."

"My boss said, 'you can't just keep saying no, you've got to listen to them,'" High said.

Once he did he became a convert to the belief that cognitive computing would be the next big thing and Watson was leading the way.

Rob High

"This style of computing will be dominant in our industry and as significant as transaction processing is today," he told an audience of several hundred attendees in a keynote at the RoboBusiness event.

"Dealing with quantifiable, structured data is the biggest thing in computing today, but that will be eclipsed by cognitive computing due to the larger amount of unstructured data being produced, 80 per cent of which is in forms classical computers aren't able to derive conclusions from," he said. "What we are doing with Watson and what other vendors are doing in this space is creating a new capability to understand the human condition and to make meaningful conclusions, you're seeing examples of this with Apple's Siri and other forms of computer speech," he added.

Today's products are somewhat crude, but they will evolve, High told an audience that had no doubt heard its share of jokes about Siri and similar systems. He described IBM's experience taking Watson code into markets such as health care.

Almost always available training data is not sufficient, but it's good enough to approximate the efficiency of an entry-level employee. The systems are constantly being re-trained with live data. Through evolving reasoning strategies, they develop greater proficiency until you get comfortable deploying them in front of a human customer, usually only after a lot of interaction with human experts.

Watson borrows a mechanical body

In an interview, High described Watson as a set of underlying technologies such as machine learning "some of which have been around for decades but never brought together in this way. Each [market-focused] service is a distinct implementation, but we call them all Watson because they are all based on similar techniques," he said.

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