Why 2015 Was a Breakthrough Year in Artificial Intelligence
Why 2015 Was a Breakthrough Year in Artificial
Intelligence
Computers are “starting to open their eyes,” said a
senior fellow at Google.
By Jack Clark December 8, 2015 — 5:00 AM PST
After a half-decade of quiet breakthroughs in artificial
intelligence, 2015 has been a landmark year. Computers are smarter and learning
faster than ever.
The pace of advancement in AI is "actually speeding
up," said Jeff Dean, a senior fellow at Google. To celebrate their
achievements and plot the year ahead, Dean and many of the other top minds in
AI are convening in Montreal this week at the Neural Information Processing
Systems conference. It started in 1987 and has become a must-attend event for
many Silicon Valley companies in the last few years, thanks to the explosion in
AI. NIPS was where Facebook Chief Executive Officer Mark Zuckerberg chose in
2013 to announce the company's plans to form an AI laboratory and where a
startup named DeepMind showed off an AI that could learn to play computer games
before it was acquired by Google.
There should be plenty to discuss this week. The
unprecedented advancements in AI research this year can be attributed to a
confluence of nerdy factors. For one, cloud computing infrastructure is vastly
more powerful and affordable, with the ability to process complex information.
There are also more plentiful datasets and free or inexpensive software
development tools for researchers to work with. Thanks to this, a crucial class
of learning technology, known as neural networks, have gone from being
prohibitively expensive to relatively cheap.
That's led to rapid uptake by the tech industry's largest
companies, including Google, Facebook, and Microsoft. Each operates its own AI
lab that conducts important research in the field and publishes much of it for
the academic community to build upon. This year, Google researchers nabbed the
cover of scientific journal Nature with a system that can learn to play and
master old Atari games without directions. Facebook built a way to let
computers describe images to blind people; Microsoft showed off a new Skype
system that can automatically translate from one language to another; and IBM
singled out AI as one of its greatest potential growth areas.
Startups are also contributing meaningfully to AI.
Preferred Networks is making AI systems that will go into industrial robots
made by Japan's Fanuc, and Indico Data Labs worked with a Facebook researcher
to teach a computer how to paint faces using its own sort of imagination.
For a look at how far computer intelligence has come this
year, here are six charts that should give you a clearer picture.
Computers have become a lot better at figuring out what's
in a photo. In 2012, a team of University of Toronto researchers won the
world's top image-recognition competition. The entire team was eventually
recruited by Google, and its approach was quickly adopted by the company and
its peers. In 2015, AI systems based on the project's approach, which relies on
a technique called deep learning, have become much more accurate. In tests,
error rates are down to about 5 percent, roughly on par with a human being's
performance.
Lots of companies are embracing AI, perhaps none more
than Google. The Internet giant went from sporadic usage of deep learning in
2012 to applying it to thousands of projects this year.
Startups are adopting AI in big ways, too. CrowdFlower,
which supplies structured data to companies, said it has seen a dramatic uptick
in the amount of data being requested by businesses to help them conduct AI
research. DiffBot, another startup, is using AI to improve its automated
data-scraping tools.
A main focus of AI research is in teaching computers to
think for themselves and improvise solutions to common problems. One way to do
that is to give them a slimmed-down version of the real world, such as the
simplified environments presented in video games, then ask them to explore it
and record the results.
But the potential goes beyond games: Similar software
could be used to teach things to AI computers and help them more quickly learn
such new things as medical diagnostics, environmental science, or improved
personal recommendations.
Google's Dean likens recent advancements in AI
capabilities to evolution. "We're at this point in actual evolution where,
previously, animals didn't have eyes, and now they have eyes," he said.
"That's going to change a lot of stuff. Computers used to not be able to
see very well, and now they're starting to open their eyes."
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