This is your brain on nanotech. Stanford scientists have begun work on a project to help create nothing less than an artificial version of the human brain. The goals evoke all our notions of a sci-fi future—machines that actually can think—but the results will depend on the down-to-earth collaboration of a deep pool of researchers.
Stanford brings a conspicuous breadth of expertise to the initiative, notes Brian Wandell, chair of psychology and one of three professors at the hub of the University’s involvement. He’s teaming with Kwabena Boahen, associate professor of bioengineering, and H.-S. Philip Wong, professor of electrical engineering, in an effort coordinated by IBM, funded by a Department of Defense agency and integrated with research from other universities, including Columbia and Cornell. The first nine months of work amount to “phase zero,” Wandell says, of a long-term challenge that will draw in an array of professional and student researchers.
The ultimate assignment: figure out how to create “cognitive computing”—technology that emulates brain functions such as perception, sensation and emotion while using hardware and software of equivalent speed, efficiency, coherency and overall compactness. This is your brain on portable power.
Part of the excitement in the work stems from the fact that it’s only incredibly ambitious, rather than inconceivable. The project—part of the SyNAPSE (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) program from the Defense Advanced Research Projects Agency (DARPA)–presumes enough understanding of brain activity to try emulating it.
“We think this is a time when we know enough about the principal computational steps that the brain uses to make judgments and decisions,” says Wandell.
But to implement that understanding, Boahen and Wong explain, entirely new concepts in nanoscale circuitry and devices will have to be substituted for the transistor-packed microprocessors that have shaped contemporary electronics. The kind of technology necessary to rival the brain’s information processing will be “much smaller than you can make a transistor,” says Boahen. “The transistor has to be reinvented.”
If that happens, he says, “there’s an opportunity to make such revolutionary advances that you essentially create a whole new industry.”
Breaking away from conventional engineering is a significant part of the challenge, notes Wong. “My students are used to perfecting these little transistors. . . . They keep asking me, ‘What are we trying to do here?’ I’m telling them we have to begin to think about things we don’t normally think about.”
Stanford’s cross-disciplinary approach means Wandell, Boahen and Wong can foster that inventiveness across all prongs of the research. There’s a systems factor (vision, hearing and learning, for example), a circuits factor (to account for the relay of information that goes on neuron to neuron) and a device factor (referring to whatever gets built). “It’s not just a question of the functions you’re trying to achieve. It’s equally about the way you achieve it and the hardware you create,” says Boahen.
“What makes a brain really powerful,” he adds, “is the richness of its network. And to capture that richness we need to be able to shrink down the circuits we are building to nanoscale, in a way that requires us to take a technological leap into the 21st century.”
