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While it may sound implausible, neurons are actually very slow, at least compared to computers, says Thomas Serre, a computational neuroscience researcher at MIT. "The reason why computers seem much slower is that they are serial machines, while our brains run in parallel," he says.
FACETS is not the only group taking this approach. Researchers at Stanford University have also been creating neuronal circuits and the Defense Advanced Research Projects Agency recently started funding a similar project.
"Where FACETS is ahead of anybody else is that they use these complex synapses," says Markram. While the neurons are quite simple, he says, the synapses are designed to use a very powerful distributed algorithm--developed by Markram--called spike-timing dependent plasticity, that allows the device to learn and adapt to new situations.
Building such complex circuits has required close collaboration with neurobiologists, says Markram. In fact, the project, whose current budget is €10.5 million (US$14.1 million), relies upon the contributions of 15 scientific groups from seven different countries. Among the challenges they face is recreating the three-dimensional structure of the brain in a 2-D piece of silicon, he says.
Despite efforts to make the chips as biologically plausible as possible, Markram admits they are still crude compared to what can be achieved in simulation. "It's not a brain. It's a more of a computer processor that has some of the accelerated parallel computing that the brain has," he says.
Because of this, Markram doubts that the hardware approach will offer much insight into how the brain works. For example, unlike Blue Brain, researchers won't be able to perform "in silico" drug testing, simulating the effects of drugs on the brain. "It's more a platform for artificial intelligence than understanding biology," he says.
The FACETS group now plans to further scale up their chips, connecting a number of wafers to create a superchip with a total of a billion neurons and 1013 synapses.
Mr. Markram is very prudent and clear about his research, unlike other researchers claiming to have built artificial brains. I like it.
Even though it must take bast amounts of processing and information for a conscience to arise. Having this technology at reach hand makes me pray for the engineers to unplug the thing every night.
Why give Darwin a chance to mess with it? so next thing you know is you're getting a socket installed in the back of your neck. ;)
Sorry, but all of that effort will bring the same result as Stuart Hameroff attempt to build the quantum brain.
We could left aside the technical difficulties of the process of modelling. Brain is a dynamic net of interconnections which are reflecting something. Could researchers explain what is reflected in it?
It is impossible to have a working model of a brain without answering on that question.
Good luck, Michael
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139 Comments
memristors, anyone?
Memristors, first proposed by Prof. Chua in 1971 and recently fabricated by HP seem like they would be a natural for brain / self-organizing / learning / neural net circuitry.
Presumably simplifying and densifying the circuitry.
Any thoughts of incorporating them into this silicon circuitry?
Or even more or less substituting memristors, en masse?
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