Technology
Hive CEO Kevin Guo interview on human-powered AI
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Hive is a Silicon Valley startup that’s best known for
its AI-powered image recognition system, with customers
including NASCAR. -
The dirty little secret of artificial intelligence is
that it takes a lot of human labor to make it all work. But
Hive embraces this. -
Hive pays 600,000 workers and counting to label photos,
getting paid pennies in return. You won’t get rich, but as Guo
says, it’s a simple “game” that makes you money — what
other app on your phone can do that? -
The data gets put to use in training AI systems, at a
scale that Guo says is unmatched.
One of the worst-kept secrets in Silicon Valley is that it takes
a whole lot of human labor to make artificial
intelligence…intelligent.
The best example: When
Google’s reCAPTCHA pages ask you to identify street signs or
storefronts in photos before you can log in, you’re proving
you’re not a robot, sure. You’re also providing
valuable, human insight into what a street sign looks like, which
is extremely useful data when you’re trying to train a
self-driving car, or a smart security camera. The whole concept
was memorably
lampooned in an episode last year of HBO’s “Silicon Valley.”
Enter Hive, a Silicon Valley-based startup that’s embracing this
human element to provide AI-powered image recognition that’s
“orders of magnitude better than Google,” as cofounder Kevin Guo
puts it. Guo’s cofounder Dmitriy Karpman actually dropped out of
a prestigious PhD program at Stanford University to make Hive a
reality; Guo got his Masters degree there before entering the
tech industry.
The secret of Hive, says Guo, is that it’s turned training an AI
into a kind of game — one with real cash prizes. Over
600,000 people have signed up for Hive
Work, a smartphone app and website, to help train its AI
systems. Hive Work asks users to do things like categorize images
(a photo of a car might fall under “automobile” and “transport”),
or to transcribe a short snipped of audio, or, like Google
reCAPTCHA, to identify all the birds in a photo.
The money isn’t much, Guo acknowledges, but it adds up to “tens
of dollars” pretty quickly, and it’s easy enough that you can
“play” from your phone while you’re on your commute. And, hey,
money is money.
“What’s the alternative? Playing Candy Crush Saga and losing
money,” jokes Guo.
The collected human insight is used to train up AI systems for
customers like NASCAR, which uses the Hive Data product to track
how often and how long a corporate logo is displayed on screen
during a race, which is information that advertisers love having,
says Guo. Hive also has other AI products, including Hive
Predict, an AI-powered tool for helping companies use their data
to spot patterns.
An advantage over the heavyweights
Hive employs about 60 people, and has raised $30 million or so in
venture capital from investors including PayPal cofounder Peter
Thiel’s Founders Fund. That makes Hive a veritable David versus
Silicon Valley Goliaths like Google, which is considered the
company at the bleeding edge of what’s possible with AI.
Indeed, Guo says that if it just came down to sheer manpower,
Hive wouldn’t stand a chance. Google, Microsoft, Amazon, and
others have enticed the leading minds in AI to their sides with
hefty pay packages that are far beyond what almost any startup
could afford.
“If I tried to fight Google with PhDs, I’d lose,” says Guo.
In fact, in an indirect way, Hive couldn’t exist without Google.
The company’s underlying technology is built on a custom version
of TensorFlow, an open source artificial intelligence framework
first developed by the search giant, and released to the
community. This means that, in terms of raw technology, Hive is
definitely behind Google.
Instead, he says that the community is a big part of Hive’s edge.
The 600,000 Hive workers who help label images are tested before
they’re allowed to contribute. The system automatically slips in
a few “known” tasks to test how well they’re paying attention and
keep everyone honest. When a customer has a specific project,
like recognizing a certain logo, it gets slipped out to that
community in the form of a challenge, with payouts adjusted for
difficulty.
And so, while Hive’s underlying AI technology is actually built
on a customized version of Google’s free, open source TensorFlow
framework, Guo boasts that his company has a tremendous trove of
high-quality, human-vetted AI training data that not even the
search giant can match. Hive takes the data, trains the AI, and
provides the tools to its customers to see what it came up with.
Guo says it’s the easiest way for companies to get started with
AI.
Beyond the data, Guo says that it’s a big advantage that Hive has
sunk millions into its own server and networking infrastructure.
It means that Hive has total control over its technological
stack, Guo says, as it continues to refine its technology.
But he also says that it’s become a boon when talking to
customers, too. As the major tech titans increasingly compete
with even the largest, most established corporations, Guo says
that its customers are finding that it would be “foolish” to
trust a Google or an Amazon with the sensitive data that powers
artificial intelligence.
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