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 The goal is to challenge Google in an area the Internet search giant
has long dominated: smartphone features that give users what they
want before they ask.
As part of its push, the company is currently trying to hire at
least 86 more employees with expertise in the branch of artificial
intelligence known as machine learning, according to a recent
analysis of Apple job postings. The company has also stepped up its
courtship of machine-learning PhD's, joining Google, Amazon,
Facebook and others in a fierce contest, leading academics say.
But some experts say the iPhone maker's strict stance on privacy is
likely to undermine its ability to compete in the rapidly
progressing field.
Machine learning, which helps devices infer from experience what
users are likely to want next, relies on crunching vast troves of
data to provide unprompted services, such as the scores for a
favorite sports team or reminders of when to leave for an
appointment based on traffic.
The larger the universe of users providing data about their habits,
the better predictions can be about what an individual might want.
But Apple analyzes its users' behavior under self-imposed
constraints to better protect their data from outsiders.
That means Apple largely relies on analyzing the data on each user’s
iPhone rather than sending it to the cloud, where it can be studied
alongside information from millions of others.
"They want to make a phone that responds to you very quickly without
knowledge of the rest of the world," said Joseph Gonzalez,
co-founder of Dato, a machine learning startup. "It's harder to do
that."
BEYOND SIRI
The Cupertino-based tech titan’s strategy will come into clearer
focus on Sept. 9, when it is expected to reveal its new iPhones and
latest mobile operating system, iOS 9. Apple has promised the
release will include a variety of intelligent reminders, which
analysts expect will rival the offerings from Google's Android.
While Apple helped pioneer mobile intelligence -it’s Siri introduced
the concept of a digital assistant to consumers in 2011 - the
company has since lost ground to Google and Microsoft, whose digital
assistants have become more adept at learning about users and
helping them with their daily routines.
As users increasingly demand phones that understand them and tailor
services accordingly, Apple cannot afford to let the gap persist,
experts say. The iPhone generated almost two-thirds of Apple's
revenue in the most recent quarter, so even a small advantage for
Android poses a threat.
"What seemed like science fiction only four years ago has become an
expectation," said venture capitalist Gary Morgenthaler, who was one
of the original investors in Siri before it was acquired by Apple in
2010.
PLAYING CATCH-UP
While Apple got off to a slow start on hiring for machine learning
jobs, it is closing in on its competitors, said Oren Etzioni, who is
CEO of the Allen Institute for Artificial Intelligence and a
professor at the University of Washington.
"In the past, Apple has not been at the vanguard of machine learning
and cutting edge artificial intelligence work, but that is rapidly
changing,” he said. “They are after the best and the brightest, just
like everybody else.”
Acquisitions of startups such as podcasting app Swell, social media
analytics firm Topsy and personal assistant app Cue have also
expanded Apple’s pool of experts in the field.
Apple does not reveal the number of people working on its machine
learning efforts.
But one former Apple employee in the area, who asked not to be named
to protect professional relationships, estimated the number of
machine learning experts had tripled or quadrupled in the past few
years.
Many of the currently posted positions are slated for software
efforts, from building on Siri’s smarts to the burgeoning search
features in iOS. The company is also hiring machine learning experts
for divisions such as product marketing and retail, suggesting a
broad-based effort to capitalize on data.
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Apple’s hiring mirrors a larger hunt in Silicon Valley for people
who can help companies make sense of their huge stashes of data,
said Ali Behnam, managing partner of Riviera Partners, an executive
search firm. Data scientists are the most sought-after experts in
the market, he noted.
Asked for comment about Apple’s strategy, a company spokeswoman
pointed to statements from Craig Federighi, senior vice president of
Software Engineering, who described the release at a developers’
conference in June as “adding intelligence throughout the user
experience in a way that enhances how you use your device but
without compromising your privacy, things like improving the apps
that you use most.”
But Google and others have an edge in spotting larger trends,
meaning Apple's predictions may not be as good, said Gonzalez,
echoing a commonly held view among machine learning experts.
What’s more, there are some features for which Apple has yet to find
an answer, such as Now on Tap, which Google will release this fall.
When users press the home button, Google will scan their screens to
deliver helpful information – a user reading about an upcoming
movie, for example, might receive reviews or a list of showtimes. It
would be difficult to deliver such services without sending data to
the cloud, experts say.
ACCESS TO DATA
Some techniques Apple and Google are investing in - such as deep
learning, a hot field of machine learning that roughly simulates the
human brain so that computers can spot patterns and classify
information – require massive amounts of data that typically cannot
be crunched on the device alone.
For machine learning experts at Apple, access to data complicates
the work at every turn, former employees said. Siri enjoys some of
Apple's most liberal privacy policies, holding onto user information
for up to six months. Other services, such as Apple Maps, retain
information for as little as 15 minutes, the former employee said.
Machine learning experts who want unfettered access to data tend to
shy away from jobs at Apple, former employees say.
But Apple is strengthening ties to academia to find the talent it
will need, attending more industry conferences and discussing its
use of tools emerging from university labs, academics say.
"They are gradually engaging a little more openly," said Michael
Franklin, who directs UC Berkeley's Algorithms, Machines and People
Lab, which Apple sponsors.
And some machine learning experts might be enticed by the challenge
of matching Google's smarts amid privacy constraints, suggested John
Duchi, an assistant professor at Stanford University.
"New flavors of problems are exciting," he said.
If Apple succeeds without compromising privacy, its Mountain View
rival may face questions about its approach to analyzing users'
data.
"People might start to ask Google for more privacy," Gonzalez said.
(Reporting by Julia Love; Editing by Steve Trousdale and Sue Horton)
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