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BIG THINKER
“An ability to learn makes it possible for robots to work in the real world. They are overcoming the gap between simulation and reality.”
Tsuneo Kawatsuma, CTO and CIO of Fujitsu
The breakthrough era for machine intelligence
Image: Jacob Hodgkinson
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The breakthrough era for machine intelligence

Kenny MacIver and Minoru Okajima – September 2014

Tsuneo Kawatsuma was appointed Executive Advisor of Fujitsu in April 2015.

Digital machines are now learning and adjusting to their environments by digesting and processing vast amounts of data, says Fujitsu CTO and CIO Tsuneo Kawatsuma.

In recent years there has been a series of rapid advances in machine intelligence and robotics, as the exponential curve in computer performance has steepened, big data processing technology has matured and connectivity has become near ubiquitous. But, says Fujitsu CTO and CIO Tsuneo Kawatsuma, we are only seeing the early capabilities of machines that can learn and tackle complex cognitive tasks.

The basic concept of machines that display some aspect of human intelligence dates back to 1960s, he outlines. However, for all but the last few of the past 50 years, computer performance has not been sufficient to allow scientists to tackle many of the major challenges.

The tipping point in terms of enhanced computation, however, is just part of the story — and maybe not the main one, says Kawatsuma. “The key technology behind intelligent machines is big data,” he argues. “Without big data, no machine can learn and demonstrate intelligence.”

He cites two examples of how the ability to process an exhaustive supply of data could lead to super-human intelligence. “I’m often asked if computers could accurately predict stock prices,” he says. “My view is that it could be possible, but it presupposes that an exhaustive set of information is available.” Getting such forecast right demands not just market data, but data about anything that might impact the stock market — where the next natural disaster or terrorist incident may happen, for example, patterns of inheritance, the liquidity of all potential investors, and millions of other data points. “So prediction would be possible, but only if I had all this information to hand.”

But in other areas, however, exhaustive information can be made available, and the ability to make sense of data at vast scale is now an economic reality, he highlights.
Sentient robots

Related to that ability to digest and rapidly process vast amounts of data, the capability is now emerging to build machines that adapt to the real world around them, rather than just follow a learned mode of behavior, Kawatsuma points out.

“Robots — and indeed computers — work in the fixed world of yes-or-no decisions. But Fujitsu is developing robots that can continue to operate, even as their environment changes, by having a learning capability,” he says.

Like other companies, Fujitsu makes extensive use of industrial robots in its manufacturing plants. Those machines learn their movements and actions by simulating an initially taught action. But any small change in their environment is enough to impact their ability to function.

Moving the robot, adjusting its point of engagement even by a fraction of a millimetre, raising the room temperature can all disrupt its operation, he says. “To overcome that Fujitsu has enhanced its robots with a self-learning capability so they can learn and adjust to their own situation,” he says. “Such a learning ability makes it possible for robots to work in the real world. This generation of new machines is overcoming the gap between simulation and reality — by themselves.”

With examples like that, machines at least look like they have human intelligence and an ability to think, says Kawatsuma.

Read about the Fujitsu Technology and Service Vision

First published
September 2014
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About: Tsuneo Kawatsuma
As CTO and CIO of Fujitsu, Tsuneo Kawatsuma leads both technology and IT strategy at the ¥4.8 trillion ($46bn) Japanese ICT giant. A corporate executive officer, he reports directly to Fujitsu president Masami Yamamoto.

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