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Computers have a lot to learn from the human brain, engineers say

The year that the Institute of Electrical and Electronics Engineers (IEEE) first formed (as the American Institute of Electrical Engineers or AIEE), Chester Arthur was in the White House, the Oxford English Dictionary published its first edition, and construction began on the Statue of Liberty on what was then known as Bedloe's Island in New York Harbor.

During a meeting today commemorating the organization's 125th anniversary, scientists (all IEEE members, of course) looked to the future, describing advances in artificial intelligence, brain-machine interfaces and energy transfer.

Computers are lauded for their speed and accuracy, but they don't hold a candle to the human brain when it comes to tackling complex mathematical problems, Dharmendra Modha, director of cognitive computing at the IBM Almaden Research Center, said at today's event. The Defense Advanced Research Projects Agency (DARPA), the U.S. Defense Department's research arm, last year gave Modha and his colleagues $4.9 million for a project called "SyNAPSE," through which they are trying to reverse-engineer the brain's computational abilities to better understand its ability to sense, perceive, act, interact, and understand different stimuli.

"We have no computers today that can begin to approach the awesome power of the human mind," Modha said. A computer comparable to the human brain, he added, would need to be able to perform more than 38 thousand trillion operations per second and hold about 3,584 terabytes of memory. (IBM's BlueGene supercomputer, one of the worlds' most powerful, has a computational capability of 92 trillion operations per second and 8 terabytes of storage.)

Although the brain is still not well understood, Modha said, "there is enough quantitative data for us to be able to begin putting together the pieces." He predicted that by 2018 computers will be able to simulate the workings of the human brain, a breakthrough that will provide researchers with unprecedented insight into how the complex organ operates.

In addition to boosting computer performance, enhanced understanding of the brain will enable people to communicate directly with machines, whether they are robots or mechanized prosthetic limbs. Primates have already proved that such brain-machine interfaces are possible, Miguel Nicolelis, co-director of Duke University Medical Center's Center for Neuroengineering, said during the conference. The researcher and his colleagues last year successfully implanted electrodes in the brain of a monkey in North Carolina that enabled him to control a robot on a treadmill in Kyoto, Japan.

Nicolelis and his team have developed a microchip they expect will allow human brains to communicate with robots using only brain signals and enables the bots to return messages directly to the brain, without the use of sight or touch. Nicolelis said that he hopes the technology will be sophisticated enough to implant into a human brain by 2012 and enable a completely quadriplegic patient to walk again.

Energy proved to be another important topic, as the researchers addressed how to power the technology they're designing. Katie Hall, chief technology officer, for WiTricity Corp. in Watertown, Mass., described her company's efforts to create wireless energy transfer technology to power remote objects. The technology, developed at the Massachusetts Institute of Technology (M.I.T.), uses resonant magnetic coupling, which lets the magnetic fields of two properly designed coils (with closely matched resonant frequencies) merge into a single continuous magnetic field that can transfer power from one device to another over a distance ranging from a few inches to several feet.

Image © Scientific American

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