IBM has unveiled its first family of cognitive computer chips. IBM’s first neurosynaptic computing chips recreate the phenomena between spiking neurons and synapses in biological systems, such as the brain, through advanced algorithms and silicon circuitry.
The company says the technology could yield many orders of magnitude and less power consumption and space than used in today’s computers.
The first two prototype chips have already been fabricated and are undergoing testing.
Called cognitive computers, systems built with these chips won’t be programmed the same way traditional computers are today.
Rather, cognitive computers are expected to learn through experiences, find correlations, create hypotheses and remember – and learn from – the outcomes, mimicking the brain’s structural and synaptic plasticity.
They could play a fundamental role in the next wave of computing and communications, as evinced by the oncoming ‘internet of things’ – a world where wireless sensors and computers will communicate on a machine-to-machine basis, gathering information and making decisions without human interaction.
IBM’s cognitive computing initiative
The company and its university collaborators also announced they have been awarded about $21m in new funding from the Defense Advanced Research Projects Agency (DARPA) for Phase 2 of the Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) project.
The goal of SyNAPSE is to create a system that not only analyses complex information from multiple sensory modalities at once, but also dynamically rewires itself as it interacts with its environment – all while rivalling the brain’s compact size and low power usage. The IBM team has already successfully completed Phases 0 and 1.
“This is a major initiative to move beyond the von Neumann paradigm that has been ruling computer architecture for more than half a century,” said Dharmendra Modha, project leader for IBM Research.
“Future applications of computing will increasingly demand functionality that is not efficiently delivered by the traditional architecture. These chips are another significant step in the evolution of computers from calculators to learning systems, signalling the beginning of a new generation of computers and their applications in business, science and government.”
While they contain no biological elements, IBM’s first cognitive computing prototype chips use digital silicon circuits inspired by neurobiology to make up what is referred to as a “neurosynaptic core” with integrated memory (replicated synapses), computation (replicated neurons) and communication (replicated axons).
IBM has two working prototype designs. Both cores were fabricated in 45 nm SOI-CMOS and contain 256 neurons. One core contains 262,144 programmable synapses and the other contains 65,536 learning synapses. The IBM team has successfully demonstrated simple applications like navigation, machine vision, pattern recognition, associative memory and classification.
IBM’s overarching cognitive computing architecture is an on-chip network of light-weight cores, creating a single integrated system of hardware and software. This architecture represents a critical shift away from traditional von Neumann computing to a potentially more power-efficient architecture that has no set programming, integrates memory with processor, and mimics the brain’s event-driven, distributed and parallel processing.
IBM’s long-term goal is to build a chip system with 10bn neurons and 100trn synapses, while consuming merely one kilowatt of power and occupying less than two litres of volume.
Future chips will be able to ingest information from complex, real-world environments through multiple sensory modes and act through multiple motor modes in a co-ordinated, context-dependent manner.
For example, a cognitive computing system monitoring the world’s water supply could contain a network of sensors and actuators that constantly record and report metrics such as temperature, pressure, wave height, acoustics and ocean tide, and issue tsunami warnings based on its decision making.
Similarly, a grocer stocking shelves could use an instrumented glove that monitors sights, smells, texture and temperature to flag bad or contaminated produce. Making sense of real-time input flowing at an ever-dizzying rate would be a Herculean task for today’s computers, but would be natural for a brain-inspired system.
“Imagine traffic lights that can integrate sights, sounds and smells and flag unsafe intersections before disaster happens or imagine cognitive co-processors that turn servers, laptops, tablets and phones into machines that can interact better with their environments,” said Modha.
For Phase 2 of SyNAPSE, IBM has assembled a world-class multi-dimensional team of researchers and collaborators to achieve these ambitious goals. The team includes Columbia University, Cornell University, University of California, Merced, and University of Wisconsin, Madison.
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