SAN JOSE, Calif. — In an era when PCs perform like
supercomputers, and supercomputers carry out inhuman feats of calculation, some
of the brightest minds in Silicon Valley say there are still crucial ways in
which a computer can’t match the problem-solving abilities of our own brains.
But Wednesday, at a supercomputing conference in Portland,
Ore., a team of scientists from IBM’s Almaden Research Lab and several other
institutions are planning to announce two developments that could one day lead
to a new kind of computer — one that uses specially designed hardware and
software to mimic what’s inside our heads.
Researchers from IBM and the Lawrence Berkeley National
Laboratory say they have performed a computer simulation that matches the scale
and complexity of a cat’s brain, and project members from IBM and Stanford have
developed an algorithm for mapping the human brain at new levels of detail.
Eventually, scientists hope that detailed knowledge will help them build a
computer that replicates the more complex working of a human brain.
The developments are early milestones on a long road that
could one day yield applications for business, science or even the military.
Still, veteran computing analyst Rick Doherty at the Envisioneering Group
called the scale and significance of their progress “jaw-dropping.”
The simulation, for example, did not exactly mimic what a
real cat does in catching a mouse. But it surpassed earlier efforts that
simulated the much simpler brain structure of a creature the size of a mouse.
Researchers used an IBM supercomputer at the Lawrence
Livermore Lab to model the movement of data through a structure with 1 billion
neurons and 10 trillion synapses, which allowed them to see how information
“percolates” through a system that’s comparable to a feline cerebral
cortex.
The work is part of a federally funded effort to study
what’s known as cognitive computing, starting with what IBM project manager
Dharmendra Modha calls “reverse-engineering the human brain,” or
designing a new computer by first getting a better understanding of how the
brain works.
“The brain is amazing,” said Modha, a computer
scientist who can wax poetic about the capabilities of human gray matter.
“The brain has awe-inspiring capabilities. It can react or interact with
complex, real-world environments, in a context-dependent way. And yet it
consumes less power than a light bulb and it occupies less space than a
two-liter bottle of soda.”
A key difference between human brains and traditional
computers, Modha says, is that current computers are designed on a model that
differentiates between processing and storing data, which can lead to a lag in
updating information. The brain works on a more complex physical structure that
can integrate and react to a constant stream of sights, sounds and other
sensory information.
“The data can be very ambiguous. When we see a friend’s
face in a crowd,” Modha said, “she could be wearing a red sweater or
a blue dress, or her hair could be styled differently, but we’re able to get to
the fundamental essence of the pattern and recognize this is our friend.”
Modha imagines a cognitive computer that could analyze a
flood of constantly updated data from trading floors, banking institutions and
even real estate markets around the world — sorting through the noise to
identify key trends and their consequences. Or one that could evaluate
pollution, weather and ocean data from real-time sensors around the world, to
monitor global water supplies.
“As our digital and physical worlds collide, there is a
tsunami of information,” Modha said. “There is a need for a new kind
of intelligence that can sort through, prioritize and extract the most
important information, much like how the brain deals with sight, sounds,
tastes, touch and smell.”
A cognitive computer might also help soldiers analyze and
react to chaotic events on a battlefield. The research is the result of a $5
million grant from the Pentagon’s Defense Advanced Research Projects Agency, or
DARPA, which also funded the forerunner of the Internet. But like that earlier
work, scientists say the study of cognitive computing could lead in many
unexpected directions.
Stanford psychology professor Brian Wandell, who studies
neuroscience, was on the team that developed a new algorithm for interpreting
data from a kind of noninvasive brain scan. Using supercomputers, the team has
used that data to measure and map the structure of axons, or thin white threads
that help carry brain signals.
Understanding these structures could lead to better
knowledge of conditions such as multiple sclerosis or autism, Wandell said.
“When you see how something is laid out, you get
insights about how something actually functions,” he added. “So
seeing the wiring diagram of the brain will be helpful for understanding how
the brain functions.”
Via McClatchy-Tribune News Service.
