Energy-efficient microchips based on the human brain

Stanford bioengineers have developed faster, more energy-efficient microchips based on the human brain – 9,000 times faster and using significantly less power than a typical PC. This offers greater possibilities for advances in robotics and a new way of understanding the brain. For instance, a chip as fast and efficient as the human brain could drive prosthetic limbs that have the speed and complexity of our own actions.

In addition to modeling the human brain, Boahen is working with other Stanford researchers to adapt Neurogrid for controlling prosthetic limbs for paralyzed people. The chip would translate brain signals into movements of the limb, without overheating the brain. Another possible application is using Neurogrid to control humanoid robots.

Heidelberg University's BrainScales project has the ambitious goal of developing analog chips to mimic the behaviors of neurons and synapses. Their HICANN chip – short for High Input Count Analog Neural Network – would be the core of a system designed to accelerate brain simulations, to enable researchers to model drug interactions that might take months to play out in a compressed time frame.