IBM, with help from DARPA, has built two working prototypes of a “neurosynaptic chip.” Based on the neurons and synapses of the brain, these first-generation cognitive computing cores could represent a major leap in power, speed and efficiency
A pair of brain-inspired cognitive computer chips unveiled today could be a new leap forward — or at least a major fork in the road — in the world of computer architecture and artificial intelligence.
About a year ago, we told you about IBM’s project to map the neural circuitry of a macaque, the most complex brain networking project of its kind. Big Blue wasn’t doing it just for the sake of science — the goal was to reverse-engineer neural networks, helping pave the way to cognitive computer systems that can think as efficiently as the brain. Now they’ve made just such a system — two, actually — and they’re calling them neurosynaptic chips.
Built on 45 nanometer silicon/metal oxide semiconductor platform, both chips have 256 neurons. One chip has 262,144 programmable synapses and the other contains 65,536 learning synapses — which can remember and learn from their own actions. IBM researchers have used the compute cores for experiments in navigation, machine vision, pattern recognition, associative memory and classification, the company says. It’s a step toward redefining computers as adaptable, holistic learning systems, rather than yes-or-no calculators.
“This new architecture represents a critical shift away form today’s traditional von Neumann computers, to extremely power-efficient architecture,” Dharmendra Modha, project leader for IBM Research, said in an interview. “It integrates memory with processors, and it is fundamentally massively parallel and distributed as well as event-driven, so it begins to rival the brain’s function, power and space.”
Credit : Rebecca Boyle
