At Intel,
its People and Practices Research Group is crafting pattern-recognition
algorithms that it hopes will gracefully scale-up, as more and more consumer
electronic devices approach supercomputer speeds.
According
to Intel, by the year 2018 mobile phones will have somewhere between 4 and 10
teraflops of processing power, surpassing the speeds of room-filling
supercomputers of not so very long ago. In anticipation of these advances,
Intel's "Everyday Sensing and Perception" study aims to answer the
simple yet relevant question: "What are people going to do with these
systems when they achieve supercomputer speeds?"
Richard
Beckwith, a research psychologist at Intel's People and Practices Research
Group, explained the group's decision to develop an application now, one that uses
the same algorithms he believes will be used in the future, "but which we
can actually deploy today."
To get
under way today, Intel chose an educational application that was both practical
and immediate. By observing grade school teachers and their students working,
Intel was able to compose pattern-recognition algorithms that can be scaled up,
for eventual use by adults, by introducing computing power in increased
increments. Pattern recognition is relatively easy in a restricted domain. In
this case, using data from a video camera to distinguish between types of
"math manipulatives"—plastic coins, pyramids and colored blocks,
which are already being utilized in about 50 percent of U.S. classrooms to help teach
mathematical concepts to children.
The first
algorithm the group crafted was one that assigned children the task of sorting
coins into piles by value. For this, the group developed an application for
Intel's ClassMate
PC, a low-cost netbook-like computer whose internal camera was
modified to aim downward in front of the child to "watch" as they
performed their tasks. The ClassMate PC watched the child sort plastic coins
into like piles of pennies, nickels and quarters. If they got it right, it gave
them positive reinforcement with spoken feedback by saying that they did a good
job.
Besides
the pattern-recognition algorithm, Intel is crafting classroom management
software for the teachers that will allow them to monitor the progress of each
student even if they are working within a larger group. The students will also
be able to take their ClassMate PCs and their math manipulatives home to
perform sort and other similar tasks as homework, "something that hasn't
been possible before," said Beckwith.
The People
and Practices Research Group is also creating a pico-projector augmentation to
the system that will directly project positive and negative feedback images
onto the coins themselves, such as putting a red spotlight on coins that are
sorted incorrectly.
Beta testing
will begin in early 2010 and, if successful, will be scaled up to work on adult
applications, such as searching through video streams for photos of friends, by
the time mobile devices have reached supercomputer speeds circa 2018.
Watch a
video here of how
Intel aims to harness pocket supercomputers.
