Researchers at Sandia National Laboratories are working on a computer that can tackle real-world situations in real-time and can run on the same power as a 20-watt light bulb.
Right now the only "machine" that can handle those functions is the human brain.
Thats why scientists are trying to build a computer system that works more like a brain than a conventional computer.
"Today's computers are wonderful at bookkeeping and solving scientific problems often described by partial differential equations, but they're horrible at just using common sense, seeing new patterns, dealing with ambiguity and making smart decisions," said John Wagner, cognitive sciences manager at Sandia National Laboratories, in a statement.
Scientists at Sandia, which are two major U.S. Department of Energy research and development operations, are working on neuro-inspired computing as part of a long-term research project on future computing systems.
"We're evaluating what the benefits would be of a system like this and considering what types of devices and architectures would be needed to enable it," said Sandia microsystems researcher Murat Okandan. ""If you do conventional computing, you are doing exact computations and exact computations only.
"If you're looking at neurocomputation, you are looking at history, or memories in your sort of innate way of looking at them, then making predictions on what's going to happen next," he added. "That's a very different realm."
Neuro-computing systems are expected to be much better-suited to taking on big data problems, which the U.S. government, along with major enterprises, are working on. The systems also should be better at handling remote autonomous and semiautonomous systems that need greater, and different, computational power, as well as better energy efficiency.
Computers that function more like the human brain could better operate unmanned drones, robots and remote sensors. They also are expected to be ideal for handling complex analysis.
The systems would be able to detect patterns and anomalies, sensing what fits and what doesn't, according to Okandan.
A neuro-inspired computer would vary in its basic functioning from today's computer systems, which largely are calculating machines with a central processing unit and memory that stores a program and data. Today's machines take a command from the program and data from the memory to execute the command, one step at a time. Of course, parallel and multicore computers can do more than one thing at a time but still use the same basic approach.
However, the architecture of neuro-inspired computers is expected to be fundamentally different.
These future machines would be designed to unite processing and storage in a single network architecture "so the pieces that are processing the data are the same pieces that are storing the data, and the data will be processed with all nodes functioning concurrently," Wagner said. "It won't be a serial step-by-step process. It'll be this network processing everything all at the same time. So it will be very efficient and very quick."
A neural-based computer architecture also would have far more working connections.
Each neuron in a neural structure can have connections coming in from about 10,000 neurons, Sandia Labs explained. However, conventional computer transistors connect, on average, to four other transistors in a static pattern.
Computer scientists have focused on mimicking the brain's neural connections before but there's much more excitement about this project because of the advances being made in the field.
Despite these advances, Sandia Labs noted that researchers should be able to create the new architecture, in simple forms, in the next few years. More complex systems may still be "decades" away.
This article, Researchers mimic human brain to build a better computer, was originally published at Computerworld.com.
Sharon Gaudin covers the Internet and Web 2.0, emerging technologies, and desktop and laptop chips for Computerworld. Follow Sharon on Twitter at @sgaudin, on Google+ or subscribe to Sharon's RSS feed. Her email address is [email protected].
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