DARPA’s Defense Sciences Office (DSO) is supporting the Systems of Neuromorphic Adaptive Plastic Scalable Electronics, or SyNAPSE, project. It’s goal, according to its April 8, 2008 BAA (Broad Agency Announcement) is to create a system with roughly: the same number of neurons (they want 10^10); same number of synapses (they want 10^14); and same power as the human brain --- that will fit in a volume of 2 liters or less, and will draw less than one kilowatt of electric power..
The SyNAPSE BAA says:
“The vision for the anticipated DARPA SyNAPSE program is the enabling of electronic neuromorphic machine technology that is scalable to biological levels. Programmable machines are limited not only by their computational capacity, but also by an architecture requiring (human-derived) algorithms to both describe and process information from their environment. In contrast, biological neural systems (e.g., brains) autonomously process information in complex environments by automatically learning relevant and probabilistically stable features and associations….
and
“Architectures will support critical structures and functions observed in biological systems such as connectivity, hierarchical organization, core component circuitry, competitive self-organization, and modulatory/reinforcement systems. As in biological systems, processing will necessarily be maximally distributed, nonlinear, and inherently noise- and defect-tolerant. “
Guilio Tononi, who has developed “An information integration theory of consciousness” (described at http://www.biomedcentral.com/1471-2202/5/42 ), is working on the SyNAPSE project. As is stated in “Cognitive computing: Building a machine that can learn from experience” (at http://www.physorg.com/news148754667.html ), Tononi is part of a team that will be developing a prototype, small-mammal-brain-powered, neuromorphic AGI for the SyNAPSE project.
“Tononi, professor of psychiatry at the UW-Madison School of Medicine and Public Health and an internationally known expert on consciousness, is part of a team of collaborators from top institutions who have been awarded a $4.9 million grant from the Defense Advanced Research Projects Agency (DARPA) for the first phase of DARPA's Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) project.
“Tononi and scientists from Columbia University and IBM will work on the "software" for the thinking computer, while nanotechnology and supercomputing experts from Cornell, Stanford and the University of California-Merced will create the "hardware." Dharmendra Modha of IBM is the principal investigator.
'The idea is to create a computer capable of sorting through multiple streams of changing data, to look for patterns and make logical decisions.
“There's another requirement: The finished cognitive computer should be as small as a the brain of a small mammal and use as little power as a 100-watt light bulb. It's a major challenge. But it's what our brains do every day.”
One of the keys to making the types of compact, low-power, extremely powerful supercomputers SyNAPSE envisions within in this coming decade is the “memsistor.”
This is because memristors enable a synapse to be modeled much more compactly than ever before possible. Memristors are a type of resistor in which the resistance can be varied by changing the magnitude or direction of current passed through it, and can be remembered until the next time it is changed. Hewlet-Packard is currently the world’s leading developer of memsistor technology and is an important part of the DARPA’s SyNAPSE program.
An article at http://www.newscientist.com/article/mg20327151.600-memristor-minds-the-future-of-artificial-intelligence.html?full=true&print=true states the following about the role of memristors in the SyNAPSE project:
“So now we've found [memristors], might a new era in artificial intelligence be at hand? The Defense Advanced Research Projects Agency certainly thinks so. DARPA is a US Department of Defense outfit with a strong record in backing high-risk, high-pay-off projects - things like the internet. In April last year, it announced the Systems of Neuromorphic Adaptive Plastic Scalable Electronics Program, SyNAPSE for short, to create "electronic neuromorphic machine technology that is scalable to biological levels".
“Williams's team from Hewlett-Packard is heavily involved. Late last year, in an obscure US Department of Energy publication called SciDAC Review, his colleague Greg Snider set out how a memristor-based chip might be wired up to test more complex models of synapses. He points out that in the human cortex synapses are packed at a density of about 10^10 per square centimetre, whereas today's microprocessors only manage densities 10 times less. "That is one important reason intelligent machines are not yet walking around on the street," he says.
'Snider's dream is of a field he calls "cortical computing" that harnesses the possibilities of memristors to mimic how the brain's neurons interact. It's an entirely new idea. "People confuse these kinds of networks with neural networks," says Williams. But neural networks - the previous best hope for creating an artificial brain - are software working on standard computing hardware. "What we're aiming for is actually a change in architecture," he says.
'The first steps are already being taken. Williams and Snider have teamed up with Gail Carpenter and Stephen Grossberg at Boston University, who are pioneers in reducing neural behaviours to systems of differential equations, to create hybrid transitor-memristor chips designed to reproduce some of the brain's thought processes. Di Ventra and his colleague Yuriy Pershin have gone further and built a memristive synapse that they claim behaves like the real thing(www.arxiv.org/abs/0905.2935).
'The electronic brain will be a time coming. "We're still getting to grips with this chip," says Williams. Part of the problem is that the chip is just too intelligent - rather than a standard digital pulse it produces an analogue output that flummoxes the standard software used to test chips. So Williams and his colleagues have had to develop their own test software. "All that takes time," he says.”
Two recent articles point out successes HP is making in developing memristors. This progress is so impressive that memristors may well become the major form of long anticipated “universal” memories (i.e., memory that can be used substantially like SRAM, DRAM, and flash are today. But first ways will have to be found to substantially increase how many times memsistor can have their values changed far beyond the number of times flash memory can be changed. People at HP currently claim to be confidient they can achieve such increases.
An April 7, 2010 NYTimes article (at http://www.nytimes.com/2010/04/08/science/08chips.html ) reported Hewlett-Packard has been making significant progress on memsistor technology. In part it said:
“they had devised a new method for storing and retrieving information from a vast three-dimensional array of memristors. The scheme could potentially free designers to stack thousands of switches in a high-rise fashion, permitting a new class of ultradense computing devices even after two-dimensional scaling reaches fundamental limits”
“The most advanced transistor technology today is based on minimum feature sizes of 30 to 40 nanometers…and Dr. Williams said that H.P. now has working 3-nanometer memristors that can switch on and off in about a nanosecond, or a billionth of a second.
'He said the company could have a competitor to flash memory in three years that would have a capacity of 20 gigabytes a square centimeter.”
An April 9, 3010 article from EEtimes (at http://www.eetimes.com/showArticle.jhtml?articleID=224202453 ) stated
“Hewlett-Packard has demonstrated memristors ("memory resistors") cast in an architecture that can be dynamically changed between logic operations and memory storage. The configurable architecture demonstrates "stateful logic" that HP claims could someday obsolete the dedicated central-processing unit (CPU) by enabling dynamically changing circuits to maintain a constant memory of their state…
“… HP showed that memristive devices could use stateful logic to perform material implication—a "complete" operator that can be interconnected to create any logical operation, much as early supercomputers were made from NAND gates. Bertrand Russell espoused material implication in Principia Mathematica, the seminal primer on logic he co-authored with Alfred Whitehead, but until now engineers have largely ignored the concept.
“HP realized the material implication gate with one regular resistor connected to two memristive devices used as digital switches (low resistance for "on" and high resistance for "off"). By using three memristors, HP could have realized a NAND gate and thus re-created the conditions under which earlier supercomputers were conceived. But HP claims that material implication is better than NAND for memristive devices, because material implication gates can be cast in an architecture that uses them as either memory or logic, enabling a device whose function can be dynamically changed.”
All these article indicate advances in memristors might well hasten the day when human-level AGI’s are created.
For more information on the SyNAPSE project look at the following two links
IBM also has part of the SyNAPSE contract as is discussed in the last half of http://www-03.ibm.com/press/us/en/pressrelease/28842.wss
For DSO’s current brief summary of the project see http://www.darpa.mil/dso/thrusts/bio/biologically/synapse/index.htm
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