Scientists Building Chip That Mimics Our Brains

Dennis Faas's picture

There's no denying that computers -- whether they're in desktop, laptop, smartphone, or tablet form -- are becoming both more powerful and complex. Most of the smartphones on the market today are far faster than the desktop PCs we used just a few years ago.

Still, researchers aren't convinced that today's cutting-edge computers are a match for the highly-adaptive human brain. But that could soon change, thanks to the work of a Boise State University research team.

Electrical and computer engineering faculty at the school are currently using a three-year $500,000 National Science Foundation grant to develop computing architecture that mimics the activity of the human brain.

The result could be a computer that, like humans, can learn new skills over time. (Source:

Future Computers Adapt to Their Environment

"By mimicking the brain's billions of interconnections and pattern recognition capabilities, we may ultimately introduce a new paradigm in speed and power, and potentially enable systems that include the ability to learn, adapt and respond to their environment," noted Barney Smith, the lead researcher behind the study.

The BSU team's research focuses on the memristor, an electrical component that can be programmed to accommodate changes in electrical pulse activity.

In essence, the memristor detects and adapts to alterations -- it's a concept the researchers are hoping to advance with their grant.

"By employing these models in combination with a new device technology that exhibits similar electrical response to the neural synapses, we will design entirely new computing chips that mimic how the brain processes information," Smith said. (Source:

Benefits: Longer Battery, Processor Lives

The benefits of using such new processing technology are clear: it will use far less power than existing processors and could dramatically extend the life of a computer. That could save consumers money and reduce the amount of electronics hardware destined for the dump.

Smith says his team plans to work on building an artificial neural network to test the new technology and may soon engage with neurobiologists in order to bring unique perspectives to the project.

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