Computer Chip Based On Human Brain Developed

Computer Chip Based On Human
Brain Developed
Aug. 14, 2013 — Today's computing
chips are incredibly complex and
contain billions of nano-scale
transistors, allowing for fast, high-
performance computers, pocket-sized
smartphones that far outpace early
desktop computers, and an explosion
in handheld tablets.
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Despite their ability to perform
thousands of tasks in the blink of an
eye, none of these devices even
come close to rivaling the computing
capabilities of the human brain. At
least not yet. But a Boise State
University research team could soon
change that.
Electrical and computer engineering
faculty Elisa Barney Smith, Kris
Campbell and Vishal Saxena are
joining forces on a project titled
"CIF: Small: Realizing Chip-scale Bio-
inspired Spiking Neural Networks with
Monolithically Integrated Nano-scale
Memristors."
Team members are experts in
machine learning (artificial
intelligence), integrated circuit design
and memristor devices. Funded by a
three-year, $500,000 National Science
Foundation grant, they have taken on
the challenge of developing a new
kind of computing architecture that
works more like a brain than a
traditional digital computer.
"By mimicking the brain's billions of
interconnections and pattern
recognition capabilities, we may
ultimately introduce a new paradigm
in speed and power, and potentially
enable systems that include the
ability to learn, adapt and respond to
their environment," said Barney
Smith, who is the principal
investigator on the grant.
The project's success rests on a
memristor -- a resistor that can be
programmed to a new resistance by
application of electrical pulses and
remembers its new resistance value
once the power is removed.
Memristors were first hypothesized
to exist in 1972 (in conjunction with
resistors, capacitors and inductors)
but were fully realized as nano-scale
devices only in the last decade.
One of the first memristors was built
in Campbell's Boise State lab, which
has the distinction of being one of
only five or six labs worldwide that
are up to the task.
The team's research builds on recent
work from scientists who have
derived mathematical algorithms to
explain the electrical interaction
between brain synapses and neurons.
"By employing these models in
combination with a new device
technology that exhibits similar
electrical response to the neural
synapses, we will design entirely new
computing chips that mimic how the
brain processes information," said
Barney Smith.
Even better, these new chips will
consume power at an order of
magnitude lower than current
computing processors, despite the
fact that they match existing chips in
physical dimensions. This will open
the door for ultra low-power
electronics intended for applications
with scarce energy resources, such as
in space, environmental sensors or
biomedical implants.
Once the team has successfully built
an artificial neural network, they will
look to engage neurobiologists in
parallel to what they are doing now.
A proposal for that could be written
in the coming year.
Barney Smith said they hope to send
the first of the new neuron chips out
for fabrication within weeks.
This material is based upon work
supported by the National Science
Foundation under Grant No.
CCF-1320987 to Boise State
University. Any opinions, findings,
and conclusions or recommendations
expressed in this material are those
of the authors and do not necessarily
reflect the views of the National
Science Foundation.