A New Computer Chip Functions Like a Brain, IBM Says
A New Chip Functions Like a Brain, IBM Says
By JOHN MARKOFF AUG. 7, 2014
A schematic showing the layout of the new processor,
named TrueNorth. Credit IBM
Inspired by the architecture of the brain, scientists
have developed a new kind of computer chip that uses no more power than a
hearing aid and may eventually excel at calculations that stump today’s
supercomputers.
The chip, or processor, is named TrueNorth and was
developed by researchers at IBM and detailed in an article published on
Thursday in the journal Science. It tries to mimic the way brains recognize
patterns, relying on densely interconnected webs of transistors similar to the
brain’s neural networks.
The chip’s electronic “neurons” are able to signal others
when a type of data — light, for example — passes a certain threshold. Working
in parallel, the neurons begin to organize the data into patterns suggesting
the light is growing brighter, or changing color or shape.
The processor may thus be able to recognize that a woman
in a video is picking up a purse, or control a robot that is reaching into a
pocket and pulling out a quarter. Humans are able to recognize these acts
without conscious thought, yet today’s computers and robots struggle to
interpret them.
A silicon chip relies on webs of transistors similar to
the brain’s neural networks. Credit I.B.M.
The chip contains 5.4 billion transistors, yet draws just
70 milliwatts of power. By contrast, modern Intel processors in today’s
personal computers and data centers may have 1.4 billion transistors and
consume far more power — 35 to 140 watts.
Today’s conventional microprocessors and graphics
processors are capable of performing billions of mathematical operations a
second, yet the new chip system clock makes its calculations barely a thousand
times a second. But because of the vast number of circuits working in parallel,
it is still capable of performing 46 billion operations a second per watt of
energy consumed, according to IBM researchers.
The TrueNorth has one million “neurons,” about as complex
as the brain of a bee.
“It is a remarkable achievement in terms of scalability
and low power consumption,” said Horst Simon, deputy director of the Lawrence
Berkeley National Laboratory.
He compared the new design to the advent of parallel
supercomputers in the 1980s, which he recalled was like moving from a two-lane
road to a superhighway.
The new approach to design, referred to variously as
neuromorphic or cognitive computing, is still in its infancy, and the IBM chips
are not yet commercially available. Yet the design has touched off a vigorous debate
over the best approach to speeding up the neural networks increasingly used in
computing.
The idea that neural networks might be useful in
processing information occurred to engineers in the 1940s, before the invention
of modern computers. Only recently, as computing has grown enormously in memory
capacity and processing speed, have they proved to be powerful computing tools.
In recent years, companies including Google, Microsoft
and Apple have turned to pattern recognition driven by neural networks to
vastly improve the quality of services like speech recognition and photo
classification.
But Yann LeCun, director of artificial intelligence
research at Facebook and a pioneering expert in neural networks, said he was
skeptical that IBM’s approach would ever outpace today’s fastest commercial
processors.
“The chip appears to be very limited in many ways, and
the performance is not what it seems,” Mr. LeCun wrote in an email sent to
journalists. In particular, he criticized as inadequate the testing of the
chip’s ability to detect moving pedestrians and cars.
“This particular task,” he wrote, “won’t impress anyone
in computer vision or machine learning.” Mr. LeCun said that while
special-purpose chips running neural networks might be useful for a range of
applications, he remained skeptical about the design IBM has chosen.
Several neuroscience researchers and computer scientists
disputed his critique.
“The TrueNorth chip is like the first transistor,” said
Terrence J. Sejnowski, director of the Salk Institute’s Computational
Neurobiology Laboratory. “It will take many generations before it can compete,
but when it does, it will be a scalable architecture that can be delivered to
cellphones, something that Yann’s G.P.U.s will never be able to do.”
G.P.U. refers to graphics processing unit, the type of
chip being used today to deliver graphics and video to computer screens and for
special processing tasks in supercomputers.
IBM’s research was funded by the Defense Advanced
Research Projects Agency, a research arm of the Pentagon, under a program
called Systems of Neuromorphic Adaptive Plastic Scalable, or SyNAPSE. According
to Gill Pratt, the program manager, the agency is pursuing twin goals in its
effort to design ultralow-power biological processors.
The first, Dr. Pratt said, is to automate some of the
surveillance done by military drones. “We have lots of data and not enough
people to look at them,” he said.
The second is to create a new kind of laboratory
instrument to allow neuroscientists to quickly test new theories about how
brains function.
A version of this article appears in print on August 8,
2014, on page B1 of the New York edition with the headline: A New Chip
Functions Like a Brain, IBM Says.
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