A new approach to A.I.: Add chaos

  • Updated: March 8, 2014 - 2:00 PM

In a new approach to artificial intelligence, anarchy helps build a thinking machine.

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Jim Gimzewski, left, and Henry Sillin at work in their lab at UCLA in Westwood, Calif., July 24, 2013. (Genaro Molina/Los Angeles Times/MCT)

Jim Gimzewski grabs a silicon wafer with a pair of tweezers and raises it to the light, thinking about Jackson Pollock, snowflakes and Tibetan mandalas.

No bigger than a quarter, the wafer looks like a small circuit board, which under a microscope is a tangle of wires randomly crisscrossed and interwoven like hairs in a tiny dust ball.

He places it inside a box the size of a mini-fridge. He closes the lid, and one of his graduate students, Henry Sillin, begins to run electricity into the box. The dust ball, messy and anarchic as it is, has come to life. Gimzewski is one step closer toward what he calls his final frontier: Building a machine that can think.

His tousled hair, Scottish brogue and clandestine pack of Marlboros would give an impression of a hip madness to the claim — if the science weren’t working so well. “We should have walked away,” Sillin says, “but it never failed enough for us to give up.”

‘Landscape you can’t imagine’

Gimzewski, a professor of chemistry at UCLA with more than 30 years working in the field of nanotechnology, believes that the tangled design of the chip is the reason for its resilience. The synapses of the brain are, after all, similarly organic and just as untidy.

Colleagues have been skeptical. Yet Gimzewski has faith in the nature of eccentric invention. “We’re operating somewhere between chaos and order, somewhere on the edge of chaos,” he says.

Conventional computers are ideal for making precise calculations, he says, but what about computing in less predictable environments? He speculates about the chip’s potential for predicting the patterns of a forest fire or the gyrations in the stock market, even for operating a driverless car.

He has reason to be encouraged. In one test, the dust ball demonstrated one of the hallmarks of intelligence. Without a program, without an integrated circuit, no lines of code or algorithm to provide a timely prompt — it was able to remember.

Before coming to UCLA in 2001, Gimzewski, 62, worked nearly 20 years with IBM’s research laboratory in Zurich. Under the guidance of Nobel laureate Heinrich Rohrer, Gimzewski explored the inner recesses of the atom. “Astronomers look at stars and discover something new,” he said. “We looked at atoms and saw a landscape you can’t imagine. At that scale you learn about relationships, how it’s all interconnected.”

Zurich was a big step for the man who grew up in Glasgow, Scotland. His neighborhood was grim, he says, recalling the street gangs he tried to dodge. His home didn’t have a telephone until he was 15. He found refuge in museums and work in a gas station. He spent his money on West Coast rock: records by Frank Zappa, Captain Beefheart.

‘Randomness is needed’

To explain his research into the dust ball, Gimzewski starts scribbling on a white board. He begins with Alan Turing, who in 1950 raised the question that has provoked scientists ever since: “Can machines think?”

The quest for artificial intelligence took the human brain as its model, and its early proponents believed that computers would provide the answer to Turing’s question. But Gimzewski thinks they had it wrong, even as the quest for artificial intelligence continues to push ahead with more sophisticated software.

But intelligence, Gimzewski says, is the ability to adapt to surroundings, learn from mistakes, draw conclusions and react without instructions, no matter the consequences. “Randomness is needed for intelligence,” says Robert Kozma, a collaborator with Gimzewski and a professor of mathematics at the University of Memphis.

Gimzewski says, “Research is about making discoveries by doing the crazy things that most people say won’t work.”



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  • Dr. Jim Gimzewski holds a petri dish of silicon computer chips that are being used in his experiment to build a computer with the computational power of the brain in his lab at UCLA in Westwood, Calif., July 24, 2013. (Genaro Molina/Los Angeles Times/MCT)

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