According to a press release that crossed the wire today, IBM researchers have been able to develop prototype processors that function less like current CPUs and more like a human brain. The experimental chips are reportedly designed to emulate a brain’s abilities for perception, action and cognition. The so called neurosynaptic computing chips were designed to recreate the relationship between spiking neurons and synapses in biological systems, like the human brain. The chips do not contain any biological elements, however, but rather function using advanced embedded algorithms and custom silicon circuitry. IBM’s first two prototype chips have already been fabricated using 45 nm SOI-CMOS process technology and are currently undergoing testing. The chips contain 256 silicon neurons and one core contains 262,144 programmable “synapses”, the other 65,536 learning “synapses”. In lieu of current programming models, future system built using this type of chip are expected to learn through experiences, find correlations, create hypotheses, and remember mimicking a biological brain. The team at IBM has successfully demonstrated simple applications like navigation, machine vision, pattern recognition, associative memory and classification already. And the company’s long-term goal is to build a chip system with ten billion neurons and a hundred trillion synapses, while consuming only one kilowatt of power and occupying less than two liters of volume.
IBM Unveils Cognitive Computing Chips
ARMONK, N.Y., - 18 Aug 2011: Today, IBM (NYSE: IBM) researchers unveiled a new generation of experimental computer chips designed to emulate the brain’s abilities for perception, action and cognition. The technology could yield many orders of magnitude less power consumption and space than used in today’s computers. In a sharp departure from traditional concepts in designing and building computers, 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. Its first two prototype chips have already been fabricated and are currently 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 brains structural and synaptic plasticity. To do this, IBM is combining principles from nanoscience, neuroscience and supercomputing as part of a multi-year cognitive computing initiative. The company and its university collaborators also announced they have been awarded approximately $21 million 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 analyzes complex information from multiple sensory modalities at once, but also dynamically rewires itself as it interacts with its environment – all while rivaling 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, signaling the beginning of a new generation of computers and their applications in business, science and government.”
One Of IBM Prototype Cognitive Computing Chips
Neurosynaptic Chips 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 ten billion neurons and hundred trillion synapses, while consuming merely one kilowatt of power and occupying less than two liters of volume. Why Cognitive Computing 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. IBM’s cognitive computing chips were built at its highly advanced chip-making facility in Fishkill, N.Y. and are currently being tested at its research labs in Yorktown Heights, N.Y. and San Jose, Calif.
This is absolutely amazing. I recently took a philosophy class on Mind and Machine where we debated if this type of breakthrough was possible. This is just the starting point for human like artificial intelligence and these types of projects are going to change the world in ways that we as humans cannot even imagine. The scary part of course is when super-intelligence starts designing other machine intelligence.
Man, it's shame it's only the beginning. of neural computing.
Fun fact: Earth worms have one of the smallest number of neurons for any living creature. They have 700 neurons. human has an estimated somewhere in the neighborhood of 100billion and 1000 times that number of synapses. these processors are a step in the right direction, but not enough for intelligent processing.
They're using memristors to create a fuzzy logic chip capable of recursive functions. A single memristor can be used as a nonvolatile memory and three can be "programmed" on the fly to form a molecular scale transistor. The idea is to cram as much neuromorphic functionality into as little space as possible.
The complexity of the architecture is just mind boggling, but this still represents the microprocessor industry's traditional brute force approach to problem solving. The mathematics and theory to predict the best ways to do such things just doesn't exist yet so, instead, they studied the brain of a cat to get an idea how the basic networks in a mammalian brain work. Since the theory can't make predictions about such large networks, having a cheap chip that can do what now requires a supercomputer to model will promote more progress in multicore computing and heterogeneous architecture among other things.
What most people will notice, of course, will be a revolution in robotics. Robots that can be taught how to chew gum and walk at the same time without falling over and bumping into things. Exactly what other things they might be capable of is anyone's guess, but it is very likely within the next ten to twenty years we can expect to witness the beginning of a new stage in the industrial revolution.
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