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Next Are Coumputers That Learn From Their Mistakes


Computers have entered the age when they are able to learn from their own mistakes, a development that is about to turn the digital world on its head.

The first commercial version of the new kind of computer chip is scheduled to be released in 2014. Not only can it automate tasks that now require painstaking programming — for example, moving a robot's arm smoothly and efficiently — but it can also sidestep and tolerate errors, potentially making the term "computer crash" obsolete.

The approach, already in use by some technology companies, is based on the biological nervous system, specifically on how neurons react to stimuli and connect with other neurons to interpret information. It allows computers to absorb new information while carrying out a task, and adjust what they do based on the changing signals.

In coming years, the approach will make possible a generation of artificial intelligence systems that will perform functions that humans do with ease: see, speak, listen, navigate and control. That can hold enormous consequences for tasks like facial and speech recognition, navigation and planning, which are in elementary stages and rely heavily on human programming.

Designers say the computing style can clear the way for robots that can walk and drive in the physical world, though a thinking computer, a staple of science fiction, is still far off.

"We're moving from engineering computing systems to something that has many of the characteristics of biological computing," said Larry Smarr, who heads the California Institute for Telecommunications and Information Technology.

Conventional computers are limited by what they have been programmed to do. Computer vision systems, for example, only "recognize" objects that can be identified by the statistics-oriented algorithms programmed into them. An algorithm is a set of step-by-step instructions to perform a calculation.

Last year, Google was able to get a machine-learning algorithm, known as a neural network, to perform an identification task without supervision. In June, the company said it had used those neural network techniques to develop a new search service to help customers find specific photos more accurately. These new approaches are being driven by the explosion of scientific knowledge about the brain.
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