Research
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 ten billion neurons and hundred trillion 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 coordinated, 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 Dr. 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.
IBM has a rich history in the area of artificial
intelligence research going all the way back to 1956 when IBM performed the world’s first large-scale (512 neuron) cortical simulation. Most recently, IBM Research scientists created Watson, an analytical computing system that specializes in understanding natural human language and provides specific answers to complex questions at rapid speeds. Watson represents a tremendous breakthrough in computers understanding natural language, “real language” that is not specially designed or encoded just for computers, but language that humans use to naturally capture and communicate knowledge.
© 2011 Angel Business Communications. Permission required.
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www.euroasiasemiconductor.com Issue IV 2011
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