Imagine a computer that can process text, video and audio in an instant, solve problems on the fly, and do it all while consuming just 10 watts of power.
It would be the ultimate computing machine if it were built with silicon instead of human nerve cells.
Compare that to current computers, which require extensive, custom programming for each application, consume hundreds of watts in power, and are still not fast enough. So it's no surprise that some computer scientists want to go back to the drawing board and try building computers that more closely emulate nature.
"The plan is to engineer the mind by reverse-engineering the brain," says Dharmendra Modha, manager of the cognitive computing project at IBM Almaden Research Center.
In what could be one of the most ambitious computing projects ever, neuroscientists, computer engineers and psychologists are coming together in a bid to create an entirely new computing architecture that can simulate the brain's abilities for perception, interaction and cognition. All that, while being small enough to fit into a lunch box and consuming extremely small amounts of power.
The 39-year old Modha, a Mumbai, India-born computer science engineer, has helped assemble a coalition of the country's best researchers in a collaborative project that includes five universities, including Stanford, Cornell and Columbia, in addition to IBM.
The researchers' goal is first to simulate a human brain on a supercomputer. Then they plan to use new nano-materials to create logic gates and transistor-based equivalents of neurons and synapses, in order to build a hardware-based, brain-like system. It's the first attempt of its kind.
In October, the group bagged a $5 million grant from Darpa -- just enough to get the first phase of the project going. If successful, they say, we could have the basics of a new computing system within the next decade.
"The idea is to do software simulations and build hardware chips that would be based on what we know about how the brain and how neural circuits work," says Christopher Kello, an associate professor at the University of California-Merced who's involved in the project.
Computing today is based on the von Neumann architecture, a design whose building blocks -- the control unit, the arithmetic logic unit and the memory -- is the stuff of Computing 101. But that architecture presents two fundamental problems: The connection between the memory and the processor can get overloaded, limiting the speed of the computer to the pace at which it can transfer data between the two. And it requires specific programs written to perform specific tasks.
In contrast, the brain distributes memory and processing functions throughout the system, learning through situations and solving problems it has never encountered before, using a complex combination of reasoning, synthesis and creativity.
"The brain works in a massively multi-threaded way," says Charles King, an analyst with Pund-IT, a research and consulting firm. "Information is coming through all the five senses in a very nonlinear fashion and it creates logical sense out of it."
The brain is composed of billions of interlinked neurons, or nerve cells that transmit signals. Each neuron receives input from 8,000 other neurons and sends an output to another 8,000. If the input is enough to agitate the neuron, it fires, transmitting a signal through its axon in the direction of another neuron. The junction between two neurons is called a synapse, and that's where signals move from one neuron to another.
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