Chip Makers Are Adding 'Brains' Alongside Cameras' Eyes
October 04 2017 - 7:29AM
Dow Jones News
By Ted Greenwald
Chip companies are adding greater smarts to cameras, spurring a
new generation of machines that not only capture imagery but
interpret and act on what they see.
Such advances in computer vision -- the ability to extract
information from images -- can enable, say, a network of security
cameras to track a package's movement. Or, in the case of Apple
Inc.'s newly unveiled iPhone X, unlock a smartphone by recognizing
a person's face.
Alphabet Inc.'s Nest Labs in September announced a doorbell
equipped with a Qualcomm Inc. chip, a video camera and
facial-recognition software that can send an alert to a Nest mobile
app if it sees a familiar face.
The market for computer-vision systems is nascent, poised to
expand from roughly $1 billion last year to $2.6 billion in 2021,
according to International Data Corp. Emerging products such as
autonomous vehicles and personal robots portend continuing growth,
and Intel Corp., Qualcomm and other chip makers are jockeying to
supply the brains to new machines.
"These [applications] are edging into viability," said IDC
analyst Michael Palma. "Maybe not mass viability, but very, very
close."
Blue River Technology, a Silicon Valley startup acquired for
$305 million last month by Deere & Co., is using computer
vision powered by Nvidia Corp. to help lettuce farmers boost
productivity and reduce or reallocate labor costs.
Farmers tend to plant lettuce seeds densely and then thin the
overcrowded sprouts using hoes, a time-consuming operation.
Blue River's See & Spray, a rig that hitches to the back of
a tractor, uses up to two dozen cameras, each equipped with an
Nvidia computer called Jetson, to identify individual sprouts and
evaluate their distance from neighbors with quarter-inch accuracy.
Those too close together get doused automatically with a precisely
aimed shot of fertilizer, enough to kill an individual plant even
as it nourishes the field -- no manual labor required.
See & Spray can typically thin an acre of lettuce in 12
minutes, work that would take a person eight hours, according to
Richard Smith, a specialist in vegetable crop production from the
University of California, Davis. Blue River claims the machine can
increase crop yield by 10%. Deere plans to extend the technology to
other crops as part of its effort to shift agriculture from tending
fields to nurturing individual plants.
Willy Pell, who oversees new technology at Blue River, believes
machines outfitted to perceive the world and act on what they sense
without human intervention will drive the next wave of Silicon
Valley investment.
"There's a lot of humanity that's simply using eyes and hands to
do things," he said. Machines outfitted with camera eyes and
silicon brains soon will be able to take over "all kinds of
repetitive tasks."
The same technology is bringing new capabilities to consumer
products as well. Qualcomm's next-generation Snapdragon smartphone
chips will transform camera output into detailed 3-D maps, a boon
for superimposing computer-generated imagery over real-world scenes
in augmented-reality apps.
Myriad, a line of chips from Intel's Movidius division that is
designed to perform artificial-intelligence computations using very
little electrical power, has found a niche in security cameras and
drones, and is branching into medicine.
Doctor Hazel, a startup, created an AI tool using a Myriad chip
that works with a medical camera to detect skin cancers on the
spot. It diagnoses cancers with up to 85% accuracy, and that rate
should improve as the system is further trained with images of
known benign and malignant moles, according to Doctor Hazel
co-founder Mike Borozdin.
One advantage to these new computer-vision systems: They pack
enough computing horsepower to apply AI to images locally, rather
than needing to interact with remote servers. That speeds up
processing, enabling devices to work without a reliable network
connection -- for, say, a drone inspecting turbines on a wind farm
-- while avoiding the risk of exposing information that may be
private or proprietary.
Deepu Talla, Nvidia's vice president in charge of AI for
applications such as robotics and drones, believes both local and
remote processing will be necessary.
Cameras mounted on traffic lights in an urban area can, for
instance, count passing vehicles and forward their tallies to a
cloud data center that analyzes the output and controls the lights
to keep traffic flowing smoothly. Nvidia is working on similar
systems in Hangzhou, China, with Alibaba Group Holding Ltd. and in
Shenzhen, China, with Huawei Technologies Co.
"There's not enough human eyeballs available" to make sense of
all the imagery cameras will capture, said Mr. Talla. "You need
computer vision."
Write to Ted Greenwald at Ted.Greenwald@wsj.com
(END) Dow Jones Newswires
October 04, 2017 07:14 ET (11:14 GMT)
Copyright (c) 2017 Dow Jones & Company, Inc.
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