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Friday, March 21, 2008
Can a Supercomputer Think Like a Brain?
Computers have long been thought of as "electronic brains", but most scientists of course smirked at that term because the machines were very crude representations of our brains for the most part. A fairly significant number of intelligent scientists have been convinced that it could take many more generations, if at all, before we can come up with machines that can think like humans. For one, it might require far more computing power than what even the highest end computers of today have on offer; for another, the human brain is far too complex, and it is not clear to everyone that we have understood its functioning even remotely. Such thoughts however do not deter some determined folks.
In the basement of a university in Switzerland sit four black boxes, each about the size of a refrigerator, and filled with 2,000 IBM microchips stacked in repeating rows. Together they form the processing core of a machine that can handle over 20 trillion operations per second. This is Blue Brain. As their web site explains, "The Blue Brain project is the first comprehensive attempt to reverse-engineer the mammalian brain, in order to understand brain function and dysfunction through detailed simulations." This is done using a computer that has phenomenal computing power - a supercomputer, in layman's terms.
The name of the supercomputer is literal: Each of its microchips has been programmed to act just like a real neuron in a real brain. The Blue Brain team started with a neuron, a nanoscale pipette, and added some really bold thinking and advanced electronic design, and wow, they have ended up with something really commendable. The behavior of the computer replicates, with surprising precision, the cellular events unfolding inside a mind. "This is the first model of the brain that has been built from the bottom-up," says Henry Markram, a neuroscientist at Ecole Polytechnique Fédérale de Lausanne (EPFL) and the director of the Blue Brain project.
This is hardly the first time scientists have made efforts to make computers mimic the brain. All of us saw how Deep Blue, the IBM supercomputer, even beat the then world champ Gary Kasparov in the famous chess championship. But most of these efforts were aimed at computers trying to replicate human thought processes in a very narrow domain, and these domains were often dominated by quantitative logic rather than qualitative ones.
Blue Brain can certainly be thought of as being only the next effort in this continuum, but the difference is this one is biologically much closer. With previous basic structures, scientists have been able to unveil physical details, molecules, chemical pathways, enzymes and genes that power the brain. These efforts and experiments offered insights that enabled scientists in understanding what the brain does, but not how it does it. This experiment however emulates chemical signaling and actually functions as a real brain. The current simulation uses 400 segments for each neuron and they have precisely researched individual ion channels and biological functions to precisely generate the simulation.
What has been most difficult even for supercomputers so far is to understand "experience". Blue Brain, if it is to simulate our brains, needs to somehow figure out what "experiencing something" means. (A nice quote from the philosopher David Chalmers, “Experience is information from the inside; physics is information from the outside.” - Thank you, Clusterflock ). The Blue Brain team intends to succeed in this by deciphering the connection between the sensations entering the machine and the flickering voltages of its brain cells. Once the team has been able to get this correlation right (and I'm not sure this will be easy!), reversing this process should be relatively easy. If they are able to complete this cycle, the supercomputer should be in a position to generate "experieces". Fascinating!
Analogous in scope to the Genome Project, the Blue Brain will provide a huge leap in our understanding of brain function and dysfunction and help us explore solutions to intractable problems in mental health and neurological disease.
By the end of 2006, the Blue Brain project had created a model of the basic functional unit of the brain, the neocortical column. At the push of a button, the model could reconstruct biologically accurate neurons based on detailed experimental data, and automatically connect them in a biological manner, a task that involves positioning around 30 million synapses in precise 3D locations.
In November, 2007, the Blue Brain project reached an important milestone and the conclusion of its first Phase, with the announcement of an entirely new data-driven process for creating, validating, and researching the neocortical column. Blue Brain has currently simulated one column of a neocortex of a rat with 10,000 neurons and 30 million synapses - a human neocortex column has 60,000 neurons.
Impressive!
Read a nice story on Blue Brain here, more updates from the Blue Brain Project web site, and the Blue Brain IBM/EPFL page @ IBM
Other Related Web Resources
Blue Brain @ Wikipedia
Blue Brain - success?
The Blue Brain Breakthrough
Blue Brain Status and the Future of Whole Brain Simulation
A 2005 article from The Speculist
A 2005 BusinessWeek article
There's a whole range of fascinating resources on the topic of computers and human brains. We try to list some that we found most useful and interesting:
Why People Think Computers Can't - by Marvin Minsky, the renowned AI pioneer. "Today, surrounded by so many automatic machines, industrial robots. and the R2-D2's of Star Wars movies, most people think AI is much more advanced than it is. But still. many `'computer experts" don't believe that machines will ever "really think." I think those specialists are too used to explaining that there's nothing inside computers but little electric currents. This leads them to believe that there can't be room left for anything else-like minds or selves. And there are many other reasons why so many experts still maintain that machines can never be creative. intuitive. or emotional, and will never really think, believe, or understand anything. This essay explains why they are wrong. (see this article in PDF format)
Brain vs. Computers @ Neuroscience for Kids - well, this has been written for kids, but precisely for that reason, the language is so simple and easy to understand that all of us can learn something from it!
Brains Don't Learn Using 0s and 1s, but They Learn Through Shades of Grey - The processors, in our brain or in a cluster of computers, is supposed to act sequentially. Not so fast! According to a new study from Cornell University, this is not true, and our mental processing is continuous. By tracking mouse movements of students working with their computers, the researchers found that our learning process was similar to other biological organisms: we're not learning through a series of 0's and 1's. Instead, our brain is cascading through shades of grey."
Computer Intelligence in the Extra-ordinary Future - One requirement for the extraordinary future is that computers will be as smart as humans. Actually, the authors who present the extraordinary future clearly think that within the next century computers will far surpass humans in intelligence. In this chapter the writer describes their reasons for making this claim and considers whether it is plausible. In order to do this the writer considers related issues such as the nature of human intelligence, how the brain works, how computers work, realistic projections of increases in computer processing speed, and different understandings of the concept of thought.
The Chinese Room - A person inside a room gets input in the form of Chinese characters on cards, and produces output in the form of Chinese characters by looking up the input Chinese characters in a rule book (written in English) that shows him what Chinese characters to give back.? It turns out that the input Chinese characters are meaningful questions and the output Chinese characters are appropriate answers to the questions, so to an outside observer, it looks as if whatever's inside the room understands Chinese. But he doesnt: he's just following rules. MORAL: computers are like the rule-follower.? They don't understand anything, even if they appear to do so. Brief but interesting stuff discussed here titled Can Computers Think?...see a related article by John Searle Is The Brain a Digital Computer?
Most neuroscientists adhere to the pixel view of neurons, arguing that individual cells can't possibly be clever enough to make sense of subtle concepts; after all, the world's fastest supercomputers have difficulty performing that pattern-recognition feat. But Itzhak Fried, a neurosurgeon who leads this UCLA research program, believes he has found "thinking cells" in the brains of his subjects. If he's right, neuroscientists may be forced to overhaul their view of how the human brain works, says this 2005 article from MIT titled "Can A Single Brain Cell Think?"
In a new MIT study (2007), a computer model designed to mimic the way the brain itself processes visual information performs as well as humans do on rapid categorization tasks. The model even tends to make similar errors as humans, possibly because it so closely follows the organization of the brain's visual system. More from here
Human Brain Region Functions Like Digital Computer - ScienceDaily Oct., 2006 - A region of the human brain that scientists believe is critical to human intellectual abilities surprisingly functions much like a digital computer, according to psychology Professor Randall O'Reilly of the University of Colorado at Boulder. In a review of biological computer models of the brain that appeared in the Oct. 6 (2006) edition of the journal Science, O'Reilly contends that the prefrontal cortex and basal ganglia operate much like a digital computer system. More from here
10 Important Differences Between Brains and Computers - this is a phenomenally useful and entirely readable article. Please make sure you read it sometime, you will understand why we should take any claims to mimicing the brain with a huge tablespoon of salt.
An interview with John McCarthy, an AI pioneer and the person credited with coining the term Artificial Intelligence
Researchers at the MIT McGovern Institute for Brain Research have used a biological model to train a computer model to recognize objects, such as cars or people, in busy street scenes. Their innovative approach, which combines neuroscience and artificial intelligence with computer science, mimics how the brain functions to recognize objects in the real world.
When will computer hardware match the human brain? ( a 1997 paper) - This paper describes how the performance of AI machines tends to improve at the same pace that AI researchers get access to faster hardware. The processing power and memory capacity necessary to match general intellectual performance of the human brain are estimated. Based on extrapolation of past trends and on examination of technologies under development, it is predicted that the required hardware will be available in cheap machines in the 2020s.
Jeff Hawkins and his colleagues have been focused on researching the brain's neocortex, and have made significant progress in understanding how it works. Using their theory, called Hierarchical Temporal Memory, or HTM, they have created a software platform that allows anyone to build HTMs for experimentation and deployment. You don't program an HTM as you would a computer; rather you configure it with software tools, then train it by exposing it to sensory data. HTMs thus learn in much the same way that children do. HTM is a rich theoretical framework and this article provides a high level overview of the theory and technology. Details of HTM are available at Numenta. An interview with Jeff here
In the basement of a university in Switzerland sit four black boxes, each about the size of a refrigerator, and filled with 2,000 IBM microchips stacked in repeating rows. Together they form the processing core of a machine that can handle over 20 trillion operations per second. This is Blue Brain. As their web site explains, "The Blue Brain project is the first comprehensive attempt to reverse-engineer the mammalian brain, in order to understand brain function and dysfunction through detailed simulations." This is done using a computer that has phenomenal computing power - a supercomputer, in layman's terms.
The name of the supercomputer is literal: Each of its microchips has been programmed to act just like a real neuron in a real brain. The Blue Brain team started with a neuron, a nanoscale pipette, and added some really bold thinking and advanced electronic design, and wow, they have ended up with something really commendable. The behavior of the computer replicates, with surprising precision, the cellular events unfolding inside a mind. "This is the first model of the brain that has been built from the bottom-up," says Henry Markram, a neuroscientist at Ecole Polytechnique Fédérale de Lausanne (EPFL) and the director of the Blue Brain project.
This is hardly the first time scientists have made efforts to make computers mimic the brain. All of us saw how Deep Blue, the IBM supercomputer, even beat the then world champ Gary Kasparov in the famous chess championship. But most of these efforts were aimed at computers trying to replicate human thought processes in a very narrow domain, and these domains were often dominated by quantitative logic rather than qualitative ones.
Blue Brain can certainly be thought of as being only the next effort in this continuum, but the difference is this one is biologically much closer. With previous basic structures, scientists have been able to unveil physical details, molecules, chemical pathways, enzymes and genes that power the brain. These efforts and experiments offered insights that enabled scientists in understanding what the brain does, but not how it does it. This experiment however emulates chemical signaling and actually functions as a real brain. The current simulation uses 400 segments for each neuron and they have precisely researched individual ion channels and biological functions to precisely generate the simulation.
What has been most difficult even for supercomputers so far is to understand "experience". Blue Brain, if it is to simulate our brains, needs to somehow figure out what "experiencing something" means. (A nice quote from the philosopher David Chalmers, “Experience is information from the inside; physics is information from the outside.” - Thank you, Clusterflock ). The Blue Brain team intends to succeed in this by deciphering the connection between the sensations entering the machine and the flickering voltages of its brain cells. Once the team has been able to get this correlation right (and I'm not sure this will be easy!), reversing this process should be relatively easy. If they are able to complete this cycle, the supercomputer should be in a position to generate "experieces". Fascinating!
Analogous in scope to the Genome Project, the Blue Brain will provide a huge leap in our understanding of brain function and dysfunction and help us explore solutions to intractable problems in mental health and neurological disease.
By the end of 2006, the Blue Brain project had created a model of the basic functional unit of the brain, the neocortical column. At the push of a button, the model could reconstruct biologically accurate neurons based on detailed experimental data, and automatically connect them in a biological manner, a task that involves positioning around 30 million synapses in precise 3D locations.
In November, 2007, the Blue Brain project reached an important milestone and the conclusion of its first Phase, with the announcement of an entirely new data-driven process for creating, validating, and researching the neocortical column. Blue Brain has currently simulated one column of a neocortex of a rat with 10,000 neurons and 30 million synapses - a human neocortex column has 60,000 neurons.
Impressive!
Read a nice story on Blue Brain here, more updates from the Blue Brain Project web site, and the Blue Brain IBM/EPFL page @ IBM
Other Related Web Resources
Blue Brain @ Wikipedia
Blue Brain - success?
The Blue Brain Breakthrough
Blue Brain Status and the Future of Whole Brain Simulation
A 2005 article from The Speculist
A 2005 BusinessWeek article
There's a whole range of fascinating resources on the topic of computers and human brains. We try to list some that we found most useful and interesting:
Why People Think Computers Can't - by Marvin Minsky, the renowned AI pioneer. "Today, surrounded by so many automatic machines, industrial robots. and the R2-D2's of Star Wars movies, most people think AI is much more advanced than it is. But still. many `'computer experts" don't believe that machines will ever "really think." I think those specialists are too used to explaining that there's nothing inside computers but little electric currents. This leads them to believe that there can't be room left for anything else-like minds or selves. And there are many other reasons why so many experts still maintain that machines can never be creative. intuitive. or emotional, and will never really think, believe, or understand anything. This essay explains why they are wrong. (see this article in PDF format)
Brain vs. Computers @ Neuroscience for Kids - well, this has been written for kids, but precisely for that reason, the language is so simple and easy to understand that all of us can learn something from it!
Brains Don't Learn Using 0s and 1s, but They Learn Through Shades of Grey - The processors, in our brain or in a cluster of computers, is supposed to act sequentially. Not so fast! According to a new study from Cornell University, this is not true, and our mental processing is continuous. By tracking mouse movements of students working with their computers, the researchers found that our learning process was similar to other biological organisms: we're not learning through a series of 0's and 1's. Instead, our brain is cascading through shades of grey."
Computer Intelligence in the Extra-ordinary Future - One requirement for the extraordinary future is that computers will be as smart as humans. Actually, the authors who present the extraordinary future clearly think that within the next century computers will far surpass humans in intelligence. In this chapter the writer describes their reasons for making this claim and considers whether it is plausible. In order to do this the writer considers related issues such as the nature of human intelligence, how the brain works, how computers work, realistic projections of increases in computer processing speed, and different understandings of the concept of thought.
The Chinese Room - A person inside a room gets input in the form of Chinese characters on cards, and produces output in the form of Chinese characters by looking up the input Chinese characters in a rule book (written in English) that shows him what Chinese characters to give back.? It turns out that the input Chinese characters are meaningful questions and the output Chinese characters are appropriate answers to the questions, so to an outside observer, it looks as if whatever's inside the room understands Chinese. But he doesnt: he's just following rules. MORAL: computers are like the rule-follower.? They don't understand anything, even if they appear to do so. Brief but interesting stuff discussed here titled Can Computers Think?...see a related article by John Searle Is The Brain a Digital Computer?
Most neuroscientists adhere to the pixel view of neurons, arguing that individual cells can't possibly be clever enough to make sense of subtle concepts; after all, the world's fastest supercomputers have difficulty performing that pattern-recognition feat. But Itzhak Fried, a neurosurgeon who leads this UCLA research program, believes he has found "thinking cells" in the brains of his subjects. If he's right, neuroscientists may be forced to overhaul their view of how the human brain works, says this 2005 article from MIT titled "Can A Single Brain Cell Think?"
In a new MIT study (2007), a computer model designed to mimic the way the brain itself processes visual information performs as well as humans do on rapid categorization tasks. The model even tends to make similar errors as humans, possibly because it so closely follows the organization of the brain's visual system. More from here
Human Brain Region Functions Like Digital Computer - ScienceDaily Oct., 2006 - A region of the human brain that scientists believe is critical to human intellectual abilities surprisingly functions much like a digital computer, according to psychology Professor Randall O'Reilly of the University of Colorado at Boulder. In a review of biological computer models of the brain that appeared in the Oct. 6 (2006) edition of the journal Science, O'Reilly contends that the prefrontal cortex and basal ganglia operate much like a digital computer system. More from here
10 Important Differences Between Brains and Computers - this is a phenomenally useful and entirely readable article. Please make sure you read it sometime, you will understand why we should take any claims to mimicing the brain with a huge tablespoon of salt.
An interview with John McCarthy, an AI pioneer and the person credited with coining the term Artificial Intelligence
Researchers at the MIT McGovern Institute for Brain Research have used a biological model to train a computer model to recognize objects, such as cars or people, in busy street scenes. Their innovative approach, which combines neuroscience and artificial intelligence with computer science, mimics how the brain functions to recognize objects in the real world.
When will computer hardware match the human brain? ( a 1997 paper) - This paper describes how the performance of AI machines tends to improve at the same pace that AI researchers get access to faster hardware. The processing power and memory capacity necessary to match general intellectual performance of the human brain are estimated. Based on extrapolation of past trends and on examination of technologies under development, it is predicted that the required hardware will be available in cheap machines in the 2020s.
Jeff Hawkins and his colleagues have been focused on researching the brain's neocortex, and have made significant progress in understanding how it works. Using their theory, called Hierarchical Temporal Memory, or HTM, they have created a software platform that allows anyone to build HTMs for experimentation and deployment. You don't program an HTM as you would a computer; rather you configure it with software tools, then train it by exposing it to sensory data. HTMs thus learn in much the same way that children do. HTM is a rich theoretical framework and this article provides a high level overview of the theory and technology. Details of HTM are available at Numenta. An interview with Jeff here
Labels: Bio-engineering, Computer-Science
PermaLink - Can a Supercomputer Think Like a Brain? posted by Ecacofonix : 12:28 AM
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Cool..This literal computer can handle 22.8 trillion operations per second.Nice, but the human brain still has it beat.The human brain has a processing capacity of 100 trillion instructions per second.
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