Today.Az » Weird / Interesting » Brain-Like computing a step closer to reality
25 June 2011 [15:11] - Today.Az
Published in the journal Advanced Materials, the study
involved the first ever demonstration of simultaneous information
processing and storage using phase-change materials. This new technique
could revolutionize computing by making computers faster and more
energy-efficient, as well as making them more closely resemble
biological systems.
Computers currently deal with processing and memory separately,
resulting in a speed and power 'bottleneck' caused by the need to
continually move data around. This is totally unlike anything in
biology, for example in human brains, where no real distinction is made
between memory and computation. To perform these two functions
simultaneously the University of Exeter research team used phase-change
materials, a kind of semi-conductor that exhibits remarkable properties.
Their study demonstrates conclusively that phase-change materials can
store and process information simultaneously. It also shows
experimentally for the first time that they can perform general-purpose
computing operations, such as addition, subtraction, multiplication and
division. More strikingly perhaps it shows that phase-change materials
can be used to make artificial neurons and synapses. This means that an
artificial system made entirely from phase-change devices could
potentially learn and process information in a similar way to our own
brains.
Lead author Professor David Wright of the University of Exeter said:
"Our findings have major implications for the development of entirely
new forms of computing, including 'brain-like' computers. We have
uncovered a technique for potentially developing new forms of
'brain-like' computer systems that could learn, adapt and change over
time. This is something that researchers have been striving for over
many years."
This study focused on the performance of a single phase-change cell.
The next stage in Exeter's research will be to build systems of
interconnected cells that can learn to perform simple tasks, such as
identification of certain objects and patterns.
This research was funded by the Engineering and Physical Sciences Research Council.
/Science Daily/
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