▲▲▲
Cognitive Computing: the breakthrough for artificial intelligence?
Cognitive Computing Chips IBM has announced, "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." The press release is lower in this post. Previously, Intel had announced a major breakthrough in microprocessors, Intel Announces Major Breakthrough in Microprocessors (Video) *Tri-Gate: world's first mass-produced 3-D transistors*.
Moving Beyond the von Neumann Paradigm 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. These are the parameters of the human brain. “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.” Also announced was 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.
SyNAPSE: IBM Cognitive Computing Project - Overview
Today's computers are little better than calculators; ruled by the von Neumann architecture for over half a century, they use storage structures and programmable memory that scientists are endlessly aiming to improve. However, the human brain - the world's most sophisticated computer - can perform complex tasks rapidly and accurately using the same amount of energy as a 20 watt light bulb and consuming as much space as a 2 liter bottle of soda. Researchers at IBM and collaborating universities are working to build cognitive systems that can learn and perform complex tasks such as action, recognition and perception, while rivaling the low energy and power consumption of the human brain.
Dr. Dharmendra Modha, IBM Cognitive Computing Manager, says today's computers, compared to the human brain, are little more than high-powered calculators. "We are trying to build cool, compact cognitive computing chips that rival the functionality of the human brain, while meeting extremely low power and low space of the human brain". Dr. Horst Simon, Deputy Director of the Lawrence Berkeley National Laboratory, says that the original computers were designed and built for one purpose (calculating). This architecture was then used for everything else in computing. Cognitive computing is rethinking the architecture of this architecture. He adds, "We don't want to build a human brain, we want to build a device that will make it easier for us to solve tasks that current computers can't solve very easily."
Dr. John Arthur, IBM Cognitive Computing Hardware, says, "The purpose of these neuromorphic chips is to build systems that can do things efficiently that current computers do poorly. Current computers are great at adding numbers, they can add billions of numbers per second, they are fantastically fast. They do really poorly at recognizing people's faces, recognizing objects, and other kinds of things that our brains do really well at. The hope is that we can build really large systems that can do recognition tasks in an automatic way." Professor Stefano Fusi, Center for Theoretical Neuroscience, Columbia University, adds, "This project (cognitive computing), is the perfect storm of nanotechnology, neuroscience, and supercomputing".
Moving Beyond the von Neumann Paradigm 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. These are the parameters of the human brain. “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.” Also announced was 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.
SyNAPSE: IBM Cognitive Computing Project - Overview
Today's computers are little better than calculators; ruled by the von Neumann architecture for over half a century, they use storage structures and programmable memory that scientists are endlessly aiming to improve. However, the human brain - the world's most sophisticated computer - can perform complex tasks rapidly and accurately using the same amount of energy as a 20 watt light bulb and consuming as much space as a 2 liter bottle of soda. Researchers at IBM and collaborating universities are working to build cognitive systems that can learn and perform complex tasks such as action, recognition and perception, while rivaling the low energy and power consumption of the human brain.
Dr. Dharmendra Modha, IBM Cognitive Computing Manager, says today's computers, compared to the human brain, are little more than high-powered calculators. "We are trying to build cool, compact cognitive computing chips that rival the functionality of the human brain, while meeting extremely low power and low space of the human brain". Dr. Horst Simon, Deputy Director of the Lawrence Berkeley National Laboratory, says that the original computers were designed and built for one purpose (calculating). This architecture was then used for everything else in computing. Cognitive computing is rethinking the architecture of this architecture. He adds, "We don't want to build a human brain, we want to build a device that will make it easier for us to solve tasks that current computers can't solve very easily."
Dr. John Arthur, IBM Cognitive Computing Hardware, says, "The purpose of these neuromorphic chips is to build systems that can do things efficiently that current computers do poorly. Current computers are great at adding numbers, they can add billions of numbers per second, they are fantastically fast. They do really poorly at recognizing people's faces, recognizing objects, and other kinds of things that our brains do really well at. The hope is that we can build really large systems that can do recognition tasks in an automatic way." Professor Stefano Fusi, Center for Theoretical Neuroscience, Columbia University, adds, "This project (cognitive computing), is the perfect storm of nanotechnology, neuroscience, and supercomputing".
SyNAPSE: IBM Cognitive Computing Project - Software
Steven Esser, IBM Research - Almaden researcher on the SyNAPSE project, walks through the transformational technology behind cognitive computing.
Steven Esser, IBM SyNAPSE researcher, says, "The current state of the art in artificial intelligence has in a way run into a wall, where artificial intelligence can produce algorithms that are very good for specific problems, but they don't generalize very well beyond those specific problems. What we're hoping is that cognitive computing will give us a whole new range of algorithms that can solve many, many different problems with only minor tweaks to the basic system. We think that is going to open up a huge number of possible innovations. What we are looking for now is a completely new way to design our computing systems, that goes beyond on the traditional way of designing computing systems."
Esser continues, "What the human brain, or any mammalian brain, can do is take in huge amounts of raw data. From that raw data, we are able to make these amazing discriminations between different objects, make associations between these different objects, and we are able to make complex decisions based on our understanding of the world - just based on that raw data. We have these new systems we can build, if we just focus on that capability. If you look at the brain, it is divided into these different areas, specialized for certain functions. We have visual areas, auditory areas, and so forth. To understand how these different parts work together, we've been able to make some simulations." These simulations follow an outside stimulus to various areas of the brain. "I think we could be seeing completely new innovative systems in the next 20 years that could revolutionize the way personal computers are built."
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.”
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. For more information about IBM Research, please visit ibm.com/research.
About IBM
The company's business model is built to support two principal goals: helping clients succeed in delivering business value by becoming more innovative, efficient and competitive through the use of business insight and information technology (IT) solutions; and, providing long-term value to shareholders. The business model has been developed over time through strategic investments in capabilities and technologies that have the best long-term growth and profitability prospects based on the value they deliver to clients. The company's strategy is to focus on the high-growth, high-value segments of the IT industry.
The company's global capabilities include services, software, hardware, fundamental research and financing. The broad mix of businesses and capabilities are combined to provide business insight and solutions for the company's clients.
The business model is flexible, and allows for periodic change and rebalancing. The company has exited commoditizing businesses like personal computers and hard disk drives, and strengthened its position through strategic investments and acquisitions in emerging higher value segments like service oriented architecture (SOA) and Information on Demand. In addition, the company has transformed itself into a globally integrated enterprise which has improved overall productivity and is driving investment and participation in the world's fastest growing markets. As a result, the company is a higher performing enterprise today than it was several years ago.
The business model, supported by the company's long-term financial model, enables the company to deliver consistently strong earnings, cash flows and returns on invested capital in changing economic environments.
Steven Esser, IBM Research - Almaden researcher on the SyNAPSE project, walks through the transformational technology behind cognitive computing.
Steven Esser, IBM SyNAPSE researcher, says, "The current state of the art in artificial intelligence has in a way run into a wall, where artificial intelligence can produce algorithms that are very good for specific problems, but they don't generalize very well beyond those specific problems. What we're hoping is that cognitive computing will give us a whole new range of algorithms that can solve many, many different problems with only minor tweaks to the basic system. We think that is going to open up a huge number of possible innovations. What we are looking for now is a completely new way to design our computing systems, that goes beyond on the traditional way of designing computing systems."
Esser continues, "What the human brain, or any mammalian brain, can do is take in huge amounts of raw data. From that raw data, we are able to make these amazing discriminations between different objects, make associations between these different objects, and we are able to make complex decisions based on our understanding of the world - just based on that raw data. We have these new systems we can build, if we just focus on that capability. If you look at the brain, it is divided into these different areas, specialized for certain functions. We have visual areas, auditory areas, and so forth. To understand how these different parts work together, we've been able to make some simulations." These simulations follow an outside stimulus to various areas of the brain. "I think we could be seeing completely new innovative systems in the next 20 years that could revolutionize the way personal computers are built."
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.”
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. For more information about IBM Research, please visit ibm.com/research.
About IBM
The company's business model is built to support two principal goals: helping clients succeed in delivering business value by becoming more innovative, efficient and competitive through the use of business insight and information technology (IT) solutions; and, providing long-term value to shareholders. The business model has been developed over time through strategic investments in capabilities and technologies that have the best long-term growth and profitability prospects based on the value they deliver to clients. The company's strategy is to focus on the high-growth, high-value segments of the IT industry.
The company's global capabilities include services, software, hardware, fundamental research and financing. The broad mix of businesses and capabilities are combined to provide business insight and solutions for the company's clients.
The business model is flexible, and allows for periodic change and rebalancing. The company has exited commoditizing businesses like personal computers and hard disk drives, and strengthened its position through strategic investments and acquisitions in emerging higher value segments like service oriented architecture (SOA) and Information on Demand. In addition, the company has transformed itself into a globally integrated enterprise which has improved overall productivity and is driving investment and participation in the world's fastest growing markets. As a result, the company is a higher performing enterprise today than it was several years ago.
The business model, supported by the company's long-term financial model, enables the company to deliver consistently strong earnings, cash flows and returns on invested capital in changing economic environments.
Visit Osprey Port News Network!
Apple, Google, Baidu, China, technology, financial system, stocks, markets, economy, science, environment, future
Follow Mountain Vision (@MountainVision) on Twitter!
Observations & thoughts by a sojourner through space & time...
Technological singularity, transhumanism, reality (objective, virtual, programmed, augmented), Universe, future.
▲▲▲
No comments:
Post a Comment