On November 20, 2008, the NY Times has published a short article entitled “Hunting for a Brainy Computer”. Steve Lohr interviews the leader of the IBM team. IBM’s Blue Gene has been used to simulate large-scale neural models (see the Blue Brain Project, led by Henry Markram). However, it is easy to mix supercomputers, IBM, and SyNAPSE in a big pot, thinking that they are the same. In reality, the Blue Gene is the example of how not to simulate the brain. This machine, as large as a room, whose power consumption is the same as the sum of the brains of a small city, can barely simulate a cortical column. As this article does not stress much (unlike other cited in this blog), the hardware problem will be solved (hopefully) by nanotechnologies, in particular by porting to nano the immense number of synapses that will link the millions of neurons implemented in the chip. No comment on “Dorothy looking for the Wizard of Oz” and “Want a really intelligent digital assistant”… It is worth mentioning that even with a chip twice the density and half the power consumption that the one SyNAPSE seeks to have in seven years available TODAY in the hands of the best modelers in the world, it is hard to think that we have the necessary modeling skills to implement that is suggested below.
Hunting for a Brainy Computer
By Steve Lohr
Want a really intelligent digital assistant?
Well, it certainly won’t be ready for this holiday season, but that is the long-range goal of a $4.9 million grant from the government’s Defense Advanced Research Projects Agency to five universities and I.B.M. Research.
The funds are for the first phase of an ambitious research venture in cognitive computing, an emerging field that lies at the outer edge of artificial intelligence. The leader of IBM’s cognitive computing program, Dharmendra Modha, describes the research as “the quest to engineer the mind by reverse-engineering the brain.”
“It’s a quest like Dorothy looking for the Wizard of Oz,” he added.
Computers excel at tasks, even daunting ones, when they work in domains with clear rules, like chess (as in I.B.M.’s Deep Blue beating the chess champion Gary Kasparov in 1997). But they do not excel at fuzzier problems, said H.-S. Philip Wong, a Stanford professor who will work on the Darpa-sponsored project. Mr. Wong cites the example of how a human devises a mental strategy for finding a car, whose exact location has been forgotten, in a busy parking lot. That task, he said, requires higher-level cognition — sensation, perception, learning and reasoning.
The time is right to pursue cognitive computing, according to Mr. Modha, because of advances in computing, nanotechnology and neuroscience. In neuroscience, for example, there has been a data-driven surge in research on neurons, synapses and neurotranmitters.
But will the brain and its workings, like so much else in biology, prove to be far more complex than foreseen, and thus resistant to the math-modeling of computer science?
That is certainly possible, Mr. Modha concedes. But all sorts of insights and new knowledge will be gleaned along the way, he says, leading to new computing products, software and sensors. I.B.M., he half-jokes, should someday stand for Intelligent Business Machines.
For the original article, click here.
Posted by Max Versace