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November 30, 2012

Spaun Brain Simulation Models Intelligence On Physiology



brain simulation ai spaun
 
Brain Simulation
Chris Eliasmith of the University of Waterloo, has led research published in the journal Science on a brain model called Spaun- the Semantic Pointer Architecture Unified Network. Spaun lives inside a computer, can view images with a camera-like eye and can draw responses to questions.
The University of Waterloo's Chris Eliasmith has spent years trying to determine what the requirements are for building a brain. He even has a book coming out in February--called “How to Build A Brain” that will look into gray matter, dendritic connections and other brain anatomy.

As he was writing it, it occurred to him that he might want to demonstrate it. So he built Spaun, the most complex simulation of a functioning brain built to date. Spaun, which stands for Semantic Pointer Architecture Unified Network, is a computer model that can recognize numbers, remember them, figure out numeric sequences, and even write them down with a robotic arm.

It’s a major breakthrough in brain simulation, because it’s the first model that can actually emulate behaviors while also modeling the physiology that underlies them.

Spaun is relatively simple, compared to real brain architecture, and it’s hard-wired, lacking the plasticity and adaptive capability human brains are known to possess. Eliasmith is working on updates that would allow it to learn new tasks and perceive instructions on a more complex level. He is even working on a program in which Spaun isn’t given explicit instructions, but rather positive or negative feedback. “We would just tell it if it is doing a good job or a bad job,” he said. “Eventually it would discover its own strategy for accomplishing its own task.”

Example input and output from Spaun. a) Handwritten numbers used as input. b) Numbers drawn by Spaun using its arm. 
Image Sounce: nengo.ca

As in the brain, Spaun's neurons communicate by changing their voltages, and the pattern of these voltage "spikes" is what carries information from one cell to another, Eliasmith said. The receiving cell generates a voltage of its own if it receives a particular voltage.

In a paper published in Science, Eliasmith and his colleagues describe "Spaun," a 2.5-million-neuron model of the brain they hope will help bridge the brain-behavior gap. Spaun, short for Semantic Pointer Architecture Unified Network, can recognize numbers, generate answers to simple numerical questions, and write them down using a physically modeled arm.

The program consists of 2.5 million simulated neurons organized into subsystems that are designed to resemble specific brain regions, including the prefrontal cortex, basil ganglia and thalamus.

Eliasmith is now working with groups in the US and Britain to try speed up Spaun and expand its tasks and behaviors.

He says such brain simulations might one day be used to better understand and model neurological disorders and diseases and to improve “machine intelligence.”

Eliasmith notes that humans have about 100 billion neurons in their brains, far more than other animals and artificial brains taking in shape in the lab.

“I think what’s special about humans is the number and connectivity of their neurons,” he says, adding that it appears the more neurons available, the more sophisticated the brain structure. “It comes down to the number of resources you have for processing information.”

Today’s “smart” machines can play chess, backgammon and act as personal assistants, like Siri on Apple’s iPhone, but Eliasmith says the processes they use have little in common with the brain.

He says it hard to predict the future, but he expects to see an explosion in artificial intelligence and more “human-like” machines.

“A robot that is able to navigate through a city and deliver a package from one place to another,” he says. “I think that kind of thing will be within reach in the next 10 years.”




SOURCES  Popular Science, NatureCNN, Nengo.ca

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