Friday, August 19, 2011 9:47:59 AM
IBM Announces Move Toward ‘Cognitive’ Computing
One of IBM’s new ‘brain-like’ chips.
IBM
By Don Clark
August 18, 2011, 2:49 AM ET
Computers are often called electronic brains, though they are different from the human variety in fundamental ways. IBM believes it is bridging the gap.
Big Blue on Thursday is announcing two experimental chips that are structured more like the brain, and could become building blocks for what IBM is calling cognitive computing. The eventual goal is to make machines that can more closely emulate the way humans perceive, learn and take action–using much less space and energy than powerful conventional computers.
“Today’s computers are with us, they wll be loved,” says Dharmendra Modha, IBM’s lead scientist on the effort. “But we are adding another member to the family.”
Modha has many metaphors for what’s involved in his work, including one that involves oranges. Today’s computers exploit processors, memory and communication links that operate at very high speed and are very efficient for some tasks. They are like farms in Florida that produce many oranges for much of the country, he says, but at a high cost in energy used for transportation.
Brains, by contrast, have simpler structures such as neurons and synapses that place processing and memory closer to each other. It’s like everybody having their own orange trees and picking their own fruit, Modha says.
IBM says both of its new exprimental chips have 256 neurons; one of them has 262,144 of what the company calls programmable synapses, while the other has 65,536 “learning” synapses. The company’s eventual goal is to build a system with ten billion neurons and a hundred trillion synapses, one that consumes a kilowatt of power and taking up less than two liters of volume.
Aren’t conventional computers already pretty powerful, and getting more so? Yes, Modha says, but some kinds of simple chores are beyond their reach.
“How about recognizing your mother’s face in a crowd?” he says. “Show me a computer that can do that.”
On a grander scale, he says, imagine scattering millions of sensors all around the world that would gather and synthesize data about wind, waves, air pressure and current flows. Such a system could produce much more accurate data about tsunamis and other phenomena, saving lives and crops, Modha says. And instead of being painstakingly programmed by people, such systems could study the real world and learn to interpret and react to it, the company says.
The idea seems to interest the U.S. government. IBM and university collaborators on Thursday are announcing that they have been awarded $21 million in a second round of funding for their research from Defense Advanced Research Projects Agency.
Though the new chips are a milestone, Modha says, he also admits truly cognitive systems are probably seven to ten years away. “But mighty oaks from little acorns grow,” he says.
Copyright ©2011 Dow Jones & Company, Inc. (emphasis added)
http://blogs.wsj.com/digits/2011/08/18/ibm-announces-move-toward-cognitive-computing/ [with comments]
===
IBM Unveils Chip Prototypes That Mimic Human Brain
IBM says the prototype “cognitive computing” chips are designed to act like a brain—to quickly collect and analyze information, make decisions based on the findings and learn from its mistakes.
By: Jeffrey Burt
2011-08-18
IBM researchers have created prototype computing chips that mirror the human brain, enabling them to not only collect and analyze information, but essentially learn from their mistakes, understand the data they're seeing and react accordingly.
The "cognitive computing" chips are able to recognize patterns and make predictions based on data, learn through experiences, find correlations among the information and remember outcomes, according to IBM officials.
The chips represent a significant departure from how computers are traditionally programmed and operated, and open opportunities in a wide range of fields, they said.
"Future applications of computing will increasingly demand functionality that is not efficiently delivered by the traditional architecture," Dharmendra Modha, project leader for IBM Research, said in a statement. "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."
IBM has been pushing efforts to drive more intelligence into an increasingly wider range of devices, and to create ways to more quickly and intelligently collect, analyze, process and respond to data. Those efforts were on public display in January when IBM's "Watson" supercomputer beat human contestants on the game show "Jeopardy."
Watson, like many projects at IBM Research Labs, is focused on analytics, or the ability to process and analyze data to arrive at the most optimal decision. Watson was a revelation because of its ability to think in a humanlike fashion and answer questions posed in natural language—with puns, riddles and nuances, etc.—by quickly running through its vast database of information, making the necessary connections and returning not with a list of possible correct answers, but the correct answer itself.
The cognitive computing chips echo those efforts. IBM officials are calling the prototypes the company's first neurosynaptic computing chips, which they said work in a fashion similar to the brain's neurons and synapses. It's done through advanced algorithms and silicon circuitry, they said.
It's through this mimicking of the brain's functionality that the chips are expected to understand, learn, predict and find correlations, according to IBM. Digital silicon circuits create what IBM is calling the chips' neurosynaptic cores, which include integrated memory (replicating synapses), computation (replicating neurons) and communication (replicating axons).
With those capabilities, computing can move away from the current if-then programming scenario and toward one where computers dynamically react, learn and problem-solve on the go.
The two working prototypes offer 45-nanometer SOI-CMOS cores that contain 256 neurons. One core contains 262,144 programmable synapses while the other holds 65,536 learning synapses. The chips are undergoing testing and have worked with simple applications such as navigation, machine vision, pattern recognition, associative memory and classification.
The effort is getting $21 million in new funding through DARPA (the Defense Advanced Research Projects Agency) for phase 2 of what IBM is calling the SyNAPSE (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) project. The project's goal is to create a computing system that not only collects and analyzes complex information gathered simultaneously from multiple sensors, but can dynamically rewire itself as it goes, and to do this in a compact, energy-efficient form factor.
IBM officials see countless applications for cognitive computing systems. In one, such a system that is used to monitor the world's water supply—collecting and analyzing such data as temperature, pressure, wave height, acoustics and ocean tides—could determine the threat of a tsunami and decide to issue a warning based on its findings. Another cognitive system could monitor sights, smells, texture and temperatures to warn grocers of bad or contaminated produce.
"Imagine traffic lights that can integrate sights, sounds and smells and flag unsafe intersections before disaster happens or imagine cognitive coprocessors that turn servers, laptops, tablets and phones into machines that can interact better with their environments," IBM's Modha said.
Copyright ©2011 Ziff Davis Enterprise Holdings Inc.
http://www.eweek.com/c/a/IT-Infrastructure/IBM-Unveils-Chip-Prototypes-That-Mimic-Human-Brain-261179/ [with comments]
===
New Chip Borrows Brain’s Computing Tricks
The SyNAPSE cognitive computer chip. The central brown core “is where the action happens,” Modha said. IBM would not release detailed diagrams because the $21 million technology is still in an experimental phase and funded by DARPA.
(IBM Research – Zurich/Flickr)
By Dave Mosher
August 18, 2011 | 3:20 pm
IBM has unveiled an experimental chip that borrows tricks from brains to power a cognitive computer, a machine able to learn from and adapt to its environment.
Reactions to the computer giant’s press release about SyNAPSE, short for Systems of Neuromorphic Adaptive Plastic Scalable Electronic [ http://www-03.ibm.com/press/us/en/pressrelease/35251.wss ], have ranged from conservative [ http://www.technologyreview.com/computing/38367/ ] to zany [ http://www.theregister.co.uk/2011/08/18/ibm_darpa_synapse_project/ ]. Some even claim it’s IBM’s attempt to recreate a cat brain from silicon.
“Each neuron in the brain is a processor and memory, and part of a social network, but that’s where the brain analogy ends. We’re not trying to simulate a brain,” said IBM spokeswoman Kelly Sims. “We’re looking to the brain to develop a system that can learn and make sense of environments on the fly.”
The human brain is a vast network of roughly 100 billion neurons sharing 100 trillion connections, called synapses. That complexity makes for more mysteries than answers — how consciousness arises, how memories are stored and why we sleep are all outstanding questions. But researchers have learned a lot about how neurons and their connections [ http://www.sciencedirect.com/science/article/pii/S0361923006002334 ] underpin the power, efficiency and adaptability of the brain.
To get a better understanding of SyNAPSE and how it borrows from organic neural networks, Wired.com spoke with project leader Dharmendra Modha [ http://www.almaden.ibm.com/cs/people/dmodha/ ] of IBM Research.
Dharmendra Modha in front of a “brain wall.”
(IBM Research – Zurich/Flickr)
Wired.com: Why do we want computers to learn and work like brains?
Dharmendra Modha: We see an increasing need for computers to be adaptable, to develop functionality today’s computers can’t. Today’s computers can carry out fast calculations. They’re left-brain computers, and are ill-suited for right-brain computation, like recognizing danger, the faces of friends and so on, that our brains do so effortlessly.
The analogy I like to use: You wouldn’t drive a car without half a brain, yet we have been using only one type of computer. It’s like we’re adding another member to the family.
Wired.com: So, you don’t view SyNAPSE [ http://www.ibm.com/smarterplanet/us/en/business_analytics/article/cognitive_computing.html ] as a replacement for modern computers?
Modha: I see each system as as complementary. Modern computers are good at some things — they have been with us since ENIAC [ http://en.wikipedia.org/wiki/ENIAC ], and I think they will be with us for perpetuity — but they aren’t well-suited for learning.
A modern computer, in its elementary form, is a block of memory and a processor separated by a bus, a communication pathway. If you want to create brain-like computation, you need to emulate the states of neurons, synapses, and the interconnections amongst neurons in the memory, the axons. You have to fetch neural states from the memory, send them to the processor across the bus, update them, send them back and store them in the memory. It’s a cycle of store, fetch, update, store … and on and on.
To deliver real-time and useful performance, you have to run this cycle very, very fast. And that leads to ever-increasing clock rates. ENIAC’s was about 100 KHz. In 1978 they were 4.7 MHz. Today’s processors are about 5 GHz. If you want faster and faster clock rates, you achieve that by building smaller and smaller devices.
Wired.com: And that’s where we run into trouble, right?
Modha: Exactly. There are two fundamental problems with this trajectory. The first is that, very soon, we will hit hard physical limits. Mother nature will stop us. Memory is the next problem. As you shorten the distance between small elements, you leak current at exponentially higher rates. At some point the system isn’t useful.
So we’re saying, let’s go back a few million years instead of ENIAC. Neurons are about 10 Hz, on average. The brain doesn’t have ever-increasing clock rates. It’s a social network of neurons.
Wired.com: What do you mean by a social network?
Modha: The links between the neurons are synapses, and that’s the important thing — how is your network wired? Who are your friends, and how close are they? You can think of the brain as a massively, massively parallel distributed computation system.
Suppose that you would like to map this computation onto one of today’s computers. They’re ill-suited for this and inefficient, so we’re looking to the brain for a different approach. Let’s build something that looks like that, on a basic level, and see how well that performs. Build a massively, massively, massively parallel distributed substrate. And that means, like in the brain, bringing your memory extremely close to a processor.
It’s like an orange farm in Florida. The trees are the memory, and the oranges are bits. Each of us, we’re the neurons who consume and process them. Now, you could be collecting them and transporting them over long distances, but imagine having your own small, private orange grove. Now you don’t have to move that data over long distances to get it. And your neighbors are nearby with their orange trees. The whole paradigm is a huge sea of synapse-like memory elements. It’s an invisible layer of processing.
Wired.com: In the brain, neural connections are plastic. They change with experience. How can something hard-wired do this?
Modha: The memory holds the synapse-like state, and it can be adapted in real-time to encode correlations, associations and causality or anti-causality. There’s a saying out there, “neurons that fire together, wire together.” The firing of neurons can strengthen or weaken synapses locally. That’s how learning is affected.
Wired.com: So let’s suppose we have a scaled-up learning computer. How do you coax it do something useful for you?
Modha: This is a platform of technology that is adaptable in ubiquitous, changing environments. Like the brain, there is almost a limitless array of applications. The brain can take information from sight, touch, sound, smell and other senses and integrate them into modalities. By modalities I mean events like speech, walking and so on.
Those modalities, the entire computation, goes back to neural connections. Their strength, their location, who is and who is not talking to whom. It is possible to reconfigure some parts of this network for different purposes. Some things are universal to all organisms with a brain — the presence of an edge, textures, colors. Even learn before you’re born, you can recognize them. They’re natural.
Knowing your mother’s face, through nurture, comes later. Imagine a hierarchy of programming techniques, a social network of chip neurons that talk and can be adapted and reconfigured to carry out tasks you desire. That’s where we’d like to end up with this.
DARPA
Wired.com © 2010 Condé Nast Digital (emphasis added)
http://www.wired.com/wiredscience/2011/08/ibm-synapse-cognitive-computer/ [with comments]
===
IBM produces first 'brain chips'
IBM's processors replicate the system of synaptic connections found in the human brain
IBM has developed a microprocessor which it claims comes closer than ever to replicating the human brain.
18 August 2011 Last updated at 09:49 ET
The system is capable of "rewiring" its connections as it encounters new information, similar to the way biological synapses work.
Researchers believe that by replicating that feature, the technology could start to learn.
Cognitive computers may eventually be used for understanding human behaviour as well as environmental monitoring.
Dharmendra Modha, IBM's project leader, explained that they were trying to recreate aspects of the mind such as emotion, perception, sensation and cognition by "reverse engineering the brain."
The SyNAPSE system uses two prototype "neurosynaptic computing chips". Both have 256 computational cores, which the scientists described as the electronic equivalent of neurons.
One chip has 262,144 programmable synapses, while the other contains 65,536 learning synapses.
Man machine
In humans and animals, synaptic connections between brain cells physically connect themselves depending on our experience of the world. The process of learning is essentially the forming and strengthening of connections.
A machine cannot solder and de-solder its electrical tracks. However, it can simulate such a system by "turning up the volume" on important input signals, and paying less attention to others.
IBM has not released exact details of how its SyNAPSE processor works, but Dr Richard Cooper, a reader in cognitive science at Birkbeck, University of London said that it likely replicated physical connections using a "virtual machine".
Instead of stronger and weaker links, such a system would simply remember how much "attention" to pay to each signal and alter that depending on new experiences.
"Part of the trick is the learning algorithm - how should you turn those volumes up and down," said Dr Cooper.
"There's a a whole bunch of tasks that can be done just with a relatively simple system like that such as associative memory. When we see a cat we might think of a mouse."
Some future-gazers in the cognitive computing world have speculated that the technology will reach a tipping point where machine consciousness is possible.
However, Dr Mark Bishop, professor of cognitive computing at Goldsmiths, was more cautious.
"[I] understand cognition to be something over and above a process simulated by the execution of mere computations, [and] see such claims as verging on the magical," he said.
IBM's work on the SyNAPSE project continues and the company, along with its academic partners, has just been awarded $21m (£12.7m) by the US Defense Advanced Research Projects Agency (DARPA).
*
Related
IBM's Watson crowned trivia king
http://www.bbc.co.uk/news/technology-12491688
*
BBC © 2011 (emphasis added)
http://www.bbc.co.uk/news/technology-14574747
===
(linked in):
http://investorshub.advfn.com/boards/read_msg.aspx?message_id=26706638 and preceding and following
http://investorshub.advfn.com/boards/read_msg.aspx?message_id=65957527 and preceding and following
One of IBM’s new ‘brain-like’ chips.
IBM
By Don Clark
August 18, 2011, 2:49 AM ET
Computers are often called electronic brains, though they are different from the human variety in fundamental ways. IBM believes it is bridging the gap.
Big Blue on Thursday is announcing two experimental chips that are structured more like the brain, and could become building blocks for what IBM is calling cognitive computing. The eventual goal is to make machines that can more closely emulate the way humans perceive, learn and take action–using much less space and energy than powerful conventional computers.
“Today’s computers are with us, they wll be loved,” says Dharmendra Modha, IBM’s lead scientist on the effort. “But we are adding another member to the family.”
Modha has many metaphors for what’s involved in his work, including one that involves oranges. Today’s computers exploit processors, memory and communication links that operate at very high speed and are very efficient for some tasks. They are like farms in Florida that produce many oranges for much of the country, he says, but at a high cost in energy used for transportation.
Brains, by contrast, have simpler structures such as neurons and synapses that place processing and memory closer to each other. It’s like everybody having their own orange trees and picking their own fruit, Modha says.
IBM says both of its new exprimental chips have 256 neurons; one of them has 262,144 of what the company calls programmable synapses, while the other has 65,536 “learning” synapses. The company’s eventual goal is to build a system with ten billion neurons and a hundred trillion synapses, one that consumes a kilowatt of power and taking up less than two liters of volume.
Aren’t conventional computers already pretty powerful, and getting more so? Yes, Modha says, but some kinds of simple chores are beyond their reach.
“How about recognizing your mother’s face in a crowd?” he says. “Show me a computer that can do that.”
On a grander scale, he says, imagine scattering millions of sensors all around the world that would gather and synthesize data about wind, waves, air pressure and current flows. Such a system could produce much more accurate data about tsunamis and other phenomena, saving lives and crops, Modha says. And instead of being painstakingly programmed by people, such systems could study the real world and learn to interpret and react to it, the company says.
The idea seems to interest the U.S. government. IBM and university collaborators on Thursday are announcing that they have been awarded $21 million in a second round of funding for their research from Defense Advanced Research Projects Agency.
Though the new chips are a milestone, Modha says, he also admits truly cognitive systems are probably seven to ten years away. “But mighty oaks from little acorns grow,” he says.
Copyright ©2011 Dow Jones & Company, Inc. (emphasis added)
http://blogs.wsj.com/digits/2011/08/18/ibm-announces-move-toward-cognitive-computing/ [with comments]
===
IBM Unveils Chip Prototypes That Mimic Human Brain
IBM says the prototype “cognitive computing” chips are designed to act like a brain—to quickly collect and analyze information, make decisions based on the findings and learn from its mistakes.
By: Jeffrey Burt
2011-08-18
IBM researchers have created prototype computing chips that mirror the human brain, enabling them to not only collect and analyze information, but essentially learn from their mistakes, understand the data they're seeing and react accordingly.
The "cognitive computing" chips are able to recognize patterns and make predictions based on data, learn through experiences, find correlations among the information and remember outcomes, according to IBM officials.
The chips represent a significant departure from how computers are traditionally programmed and operated, and open opportunities in a wide range of fields, they said.
"Future applications of computing will increasingly demand functionality that is not efficiently delivered by the traditional architecture," Dharmendra Modha, project leader for IBM Research, said in a statement. "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."
IBM has been pushing efforts to drive more intelligence into an increasingly wider range of devices, and to create ways to more quickly and intelligently collect, analyze, process and respond to data. Those efforts were on public display in January when IBM's "Watson" supercomputer beat human contestants on the game show "Jeopardy."
Watson, like many projects at IBM Research Labs, is focused on analytics, or the ability to process and analyze data to arrive at the most optimal decision. Watson was a revelation because of its ability to think in a humanlike fashion and answer questions posed in natural language—with puns, riddles and nuances, etc.—by quickly running through its vast database of information, making the necessary connections and returning not with a list of possible correct answers, but the correct answer itself.
The cognitive computing chips echo those efforts. IBM officials are calling the prototypes the company's first neurosynaptic computing chips, which they said work in a fashion similar to the brain's neurons and synapses. It's done through advanced algorithms and silicon circuitry, they said.
It's through this mimicking of the brain's functionality that the chips are expected to understand, learn, predict and find correlations, according to IBM. Digital silicon circuits create what IBM is calling the chips' neurosynaptic cores, which include integrated memory (replicating synapses), computation (replicating neurons) and communication (replicating axons).
With those capabilities, computing can move away from the current if-then programming scenario and toward one where computers dynamically react, learn and problem-solve on the go.
The two working prototypes offer 45-nanometer SOI-CMOS cores that contain 256 neurons. One core contains 262,144 programmable synapses while the other holds 65,536 learning synapses. The chips are undergoing testing and have worked with simple applications such as navigation, machine vision, pattern recognition, associative memory and classification.
The effort is getting $21 million in new funding through DARPA (the Defense Advanced Research Projects Agency) for phase 2 of what IBM is calling the SyNAPSE (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) project. The project's goal is to create a computing system that not only collects and analyzes complex information gathered simultaneously from multiple sensors, but can dynamically rewire itself as it goes, and to do this in a compact, energy-efficient form factor.
IBM officials see countless applications for cognitive computing systems. In one, such a system that is used to monitor the world's water supply—collecting and analyzing such data as temperature, pressure, wave height, acoustics and ocean tides—could determine the threat of a tsunami and decide to issue a warning based on its findings. Another cognitive system could monitor sights, smells, texture and temperatures to warn grocers of bad or contaminated produce.
"Imagine traffic lights that can integrate sights, sounds and smells and flag unsafe intersections before disaster happens or imagine cognitive coprocessors that turn servers, laptops, tablets and phones into machines that can interact better with their environments," IBM's Modha said.
Copyright ©2011 Ziff Davis Enterprise Holdings Inc.
http://www.eweek.com/c/a/IT-Infrastructure/IBM-Unveils-Chip-Prototypes-That-Mimic-Human-Brain-261179/ [with comments]
===
New Chip Borrows Brain’s Computing Tricks
The SyNAPSE cognitive computer chip. The central brown core “is where the action happens,” Modha said. IBM would not release detailed diagrams because the $21 million technology is still in an experimental phase and funded by DARPA.
(IBM Research – Zurich/Flickr)
By Dave Mosher
August 18, 2011 | 3:20 pm
IBM has unveiled an experimental chip that borrows tricks from brains to power a cognitive computer, a machine able to learn from and adapt to its environment.
Reactions to the computer giant’s press release about SyNAPSE, short for Systems of Neuromorphic Adaptive Plastic Scalable Electronic [ http://www-03.ibm.com/press/us/en/pressrelease/35251.wss ], have ranged from conservative [ http://www.technologyreview.com/computing/38367/ ] to zany [ http://www.theregister.co.uk/2011/08/18/ibm_darpa_synapse_project/ ]. Some even claim it’s IBM’s attempt to recreate a cat brain from silicon.
“Each neuron in the brain is a processor and memory, and part of a social network, but that’s where the brain analogy ends. We’re not trying to simulate a brain,” said IBM spokeswoman Kelly Sims. “We’re looking to the brain to develop a system that can learn and make sense of environments on the fly.”
The human brain is a vast network of roughly 100 billion neurons sharing 100 trillion connections, called synapses. That complexity makes for more mysteries than answers — how consciousness arises, how memories are stored and why we sleep are all outstanding questions. But researchers have learned a lot about how neurons and their connections [ http://www.sciencedirect.com/science/article/pii/S0361923006002334 ] underpin the power, efficiency and adaptability of the brain.
To get a better understanding of SyNAPSE and how it borrows from organic neural networks, Wired.com spoke with project leader Dharmendra Modha [ http://www.almaden.ibm.com/cs/people/dmodha/ ] of IBM Research.
Dharmendra Modha in front of a “brain wall.”
(IBM Research – Zurich/Flickr)
Wired.com: Why do we want computers to learn and work like brains?
Dharmendra Modha: We see an increasing need for computers to be adaptable, to develop functionality today’s computers can’t. Today’s computers can carry out fast calculations. They’re left-brain computers, and are ill-suited for right-brain computation, like recognizing danger, the faces of friends and so on, that our brains do so effortlessly.
The analogy I like to use: You wouldn’t drive a car without half a brain, yet we have been using only one type of computer. It’s like we’re adding another member to the family.
Wired.com: So, you don’t view SyNAPSE [ http://www.ibm.com/smarterplanet/us/en/business_analytics/article/cognitive_computing.html ] as a replacement for modern computers?
Modha: I see each system as as complementary. Modern computers are good at some things — they have been with us since ENIAC [ http://en.wikipedia.org/wiki/ENIAC ], and I think they will be with us for perpetuity — but they aren’t well-suited for learning.
A modern computer, in its elementary form, is a block of memory and a processor separated by a bus, a communication pathway. If you want to create brain-like computation, you need to emulate the states of neurons, synapses, and the interconnections amongst neurons in the memory, the axons. You have to fetch neural states from the memory, send them to the processor across the bus, update them, send them back and store them in the memory. It’s a cycle of store, fetch, update, store … and on and on.
To deliver real-time and useful performance, you have to run this cycle very, very fast. And that leads to ever-increasing clock rates. ENIAC’s was about 100 KHz. In 1978 they were 4.7 MHz. Today’s processors are about 5 GHz. If you want faster and faster clock rates, you achieve that by building smaller and smaller devices.
Wired.com: And that’s where we run into trouble, right?
Modha: Exactly. There are two fundamental problems with this trajectory. The first is that, very soon, we will hit hard physical limits. Mother nature will stop us. Memory is the next problem. As you shorten the distance between small elements, you leak current at exponentially higher rates. At some point the system isn’t useful.
So we’re saying, let’s go back a few million years instead of ENIAC. Neurons are about 10 Hz, on average. The brain doesn’t have ever-increasing clock rates. It’s a social network of neurons.
Wired.com: What do you mean by a social network?
Modha: The links between the neurons are synapses, and that’s the important thing — how is your network wired? Who are your friends, and how close are they? You can think of the brain as a massively, massively parallel distributed computation system.
Suppose that you would like to map this computation onto one of today’s computers. They’re ill-suited for this and inefficient, so we’re looking to the brain for a different approach. Let’s build something that looks like that, on a basic level, and see how well that performs. Build a massively, massively, massively parallel distributed substrate. And that means, like in the brain, bringing your memory extremely close to a processor.
It’s like an orange farm in Florida. The trees are the memory, and the oranges are bits. Each of us, we’re the neurons who consume and process them. Now, you could be collecting them and transporting them over long distances, but imagine having your own small, private orange grove. Now you don’t have to move that data over long distances to get it. And your neighbors are nearby with their orange trees. The whole paradigm is a huge sea of synapse-like memory elements. It’s an invisible layer of processing.
Wired.com: In the brain, neural connections are plastic. They change with experience. How can something hard-wired do this?
Modha: The memory holds the synapse-like state, and it can be adapted in real-time to encode correlations, associations and causality or anti-causality. There’s a saying out there, “neurons that fire together, wire together.” The firing of neurons can strengthen or weaken synapses locally. That’s how learning is affected.
Wired.com: So let’s suppose we have a scaled-up learning computer. How do you coax it do something useful for you?
Modha: This is a platform of technology that is adaptable in ubiquitous, changing environments. Like the brain, there is almost a limitless array of applications. The brain can take information from sight, touch, sound, smell and other senses and integrate them into modalities. By modalities I mean events like speech, walking and so on.
Those modalities, the entire computation, goes back to neural connections. Their strength, their location, who is and who is not talking to whom. It is possible to reconfigure some parts of this network for different purposes. Some things are universal to all organisms with a brain — the presence of an edge, textures, colors. Even learn before you’re born, you can recognize them. They’re natural.
Knowing your mother’s face, through nurture, comes later. Imagine a hierarchy of programming techniques, a social network of chip neurons that talk and can be adapted and reconfigured to carry out tasks you desire. That’s where we’d like to end up with this.
DARPA
Wired.com © 2010 Condé Nast Digital (emphasis added)
http://www.wired.com/wiredscience/2011/08/ibm-synapse-cognitive-computer/ [with comments]
===
IBM produces first 'brain chips'
IBM's processors replicate the system of synaptic connections found in the human brain
IBM has developed a microprocessor which it claims comes closer than ever to replicating the human brain.
18 August 2011 Last updated at 09:49 ET
The system is capable of "rewiring" its connections as it encounters new information, similar to the way biological synapses work.
Researchers believe that by replicating that feature, the technology could start to learn.
Cognitive computers may eventually be used for understanding human behaviour as well as environmental monitoring.
Dharmendra Modha, IBM's project leader, explained that they were trying to recreate aspects of the mind such as emotion, perception, sensation and cognition by "reverse engineering the brain."
The SyNAPSE system uses two prototype "neurosynaptic computing chips". Both have 256 computational cores, which the scientists described as the electronic equivalent of neurons.
One chip has 262,144 programmable synapses, while the other contains 65,536 learning synapses.
Man machine
In humans and animals, synaptic connections between brain cells physically connect themselves depending on our experience of the world. The process of learning is essentially the forming and strengthening of connections.
A machine cannot solder and de-solder its electrical tracks. However, it can simulate such a system by "turning up the volume" on important input signals, and paying less attention to others.
IBM has not released exact details of how its SyNAPSE processor works, but Dr Richard Cooper, a reader in cognitive science at Birkbeck, University of London said that it likely replicated physical connections using a "virtual machine".
Instead of stronger and weaker links, such a system would simply remember how much "attention" to pay to each signal and alter that depending on new experiences.
"Part of the trick is the learning algorithm - how should you turn those volumes up and down," said Dr Cooper.
"There's a a whole bunch of tasks that can be done just with a relatively simple system like that such as associative memory. When we see a cat we might think of a mouse."
Some future-gazers in the cognitive computing world have speculated that the technology will reach a tipping point where machine consciousness is possible.
However, Dr Mark Bishop, professor of cognitive computing at Goldsmiths, was more cautious.
"[I] understand cognition to be something over and above a process simulated by the execution of mere computations, [and] see such claims as verging on the magical," he said.
IBM's work on the SyNAPSE project continues and the company, along with its academic partners, has just been awarded $21m (£12.7m) by the US Defense Advanced Research Projects Agency (DARPA).
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Related
IBM's Watson crowned trivia king
http://www.bbc.co.uk/news/technology-12491688
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BBC © 2011 (emphasis added)
http://www.bbc.co.uk/news/technology-14574747
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Greensburg, KS - 5/4/07
"Eternal vigilance is the price of Liberty."
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upon the Right of Election, 1790
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