New York: Imagine a car that can drive
itself to your desired destination notwithstanding the traffic
and other hurdles. Scientists say this could soon be a
Researchers at Yale University and New York University
have developed a supercomputer based on human visual system
that they say could allow cars to drive themselves.
Dubbed NeuFlow, the system takes its inspiration from
the mammalian visual system, mimicking its neural network to
quickly interpret the world around it, said lead researcher
Eugenio Culurciello of Yale`s School of Engineering & Applied
Culurciello, who presented their research at the High
Performance Embedded Computing (HPEC) workshop in Boston, said
the system uses complex vision algorithms developed by Yann
LeCun at New York University to run large neural networks for
synthetic vision applications.
According to the scientists, NeuFlow processes tens of
megapixel images in real time in order to be able to recognise
the various objects encountered on the road?such as other
cars, people, stoplights, sidewalks, not to mention the road
The system is also extremely efficient, simultaneously
running more than 100 billion operations per second using only
a few watts (that?s less than the power a cell phone uses) to
accomplish what it takes bench-top computers with multiple
graphic processors more than 300 watts to achieve.
"One of our first prototypes of this system is already
capable of outperforming graphic processors on vision tasks,"
Culurciello said in a statement.
"The complete system is going to be no bigger than a
wallet, so it could easily be embedded in cars and other
Beyond the autonomous car navigation, the scientists
said, the system could be used to improve robot navigation
into dangerous or difficult-to-reach locations.
It can be used to provide 360-degree synthetic vision
for soldiers in combat situations, or in assisted living
situations where it could be used to monitor motion and call
for help should an elderly person fall, for example.