By Jeremy Hsu
Posted 29 Sep 2014 | 19:01 GMT
Neuromorphic computer chips meant to mimic the neural network architecture of biological brains have generally fallen short of their wetware counterparts in efficiency—a crucial factor that has limited practical applications for such chips. That could be changing. At a power density of just 20 milliwatts per square centimeter, IBM’s new brain-inspired chip comes tantalizingly close to such wetware efficiency. The hope is that it could bring brainlike intelligence to the sensors of smartphones, smart cars, and—if IBM has its way—everything else.
The latest IBM neurosynaptic computer chip, called TrueNorth, consists of 1 million programmable neurons and 256 million programmable synapses conveying signals between the digital neurons. Each of the chip’s 4,096 neurosynaptic cores includes the entire computing package:
- computation, and
Such architecture helps to bypass the bottleneck in traditional von Neumann computing, where program instructions and operation data cannot pass through the same route simultaneously.
“This is literally a supercomputer the size of a postage stamp, light like a feather, and low power like a hearing aid,” says Dharmendra Modha, IBM fellow and chief scientist for brain-inspired computing at IBM Research-Almaden, in San Jose, Calif.
Such chips can emulate the human brain’s ability to recognize different objects in real time; TrueNorth showed it could distinguish among pedestrians, bicyclists, cars, and trucks. IBM envisions its new chips working together with traditional computing devices as hybrid machines, providing a dose of brainlike intelligence. The chip’s architecture, developed together by IBM and Cornell University, was first detailed in August in the journal Science.