- Hive is a Silicon Valley startup that’s best clothes known for its AI-powered image recognition system, with customers involving NASCAR.
- The dirty little secret of artificial intelligence is that it engages a lot of human labor to make it all work. But Hive embraces this.
- Hive pay outs 600,000 workers and counting to label photos, getting paid pennies in pop up again. 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 figures gets put to use in training AI systems, at a scale that Guo says is unmatched.
One of the worst-kept under covers in Silicon Valley is that it takes a whole lot of human labor to hook artificial intelligence…intelligent.
The best example: When Google’s reCAPTCHA versos ask you to identify street signs or storefronts in photos before you can log in, you’re proving you’re not a myrmidon, sure. You’re also providing valuable, human insight into what a concourse sign looks like, which is extremely useful data when you’re infuriating to train a self-driving car, or a smart security camera. The whole concept was memorably lampooned in an matter last year of HBO’s “Silicon Valley.”
Enter Hive, a Silicon Valley-based startup that’s squeezing this human element to provide AI-powered image recognition that’s “commissions of magnitude better than Google,” as cofounder Kevin Guo puts it. Guo’s cofounder Dmitriy Karpman in actuality dropped out of a prestigious PhD program at Stanford University to make Hive a fact; Guo got his Masters degree there before entering the tech industry.
The hush-hush of Hive, says Guo, is that it’s turned training an AI into a kind of racket – one with real cash prizes. Over 600,000 people own signed up for Hive Work, a smartphone app and website, to help train its AI set-ups. Hive Work asks users to do things like categorize images (a photo of a car energy fall under “automobile” and “transport”), or to transcribe a short fragmented of audio, or, like Google reCAPTCHA, to identify all the birds in a photo.
The flush isn’t much, Guo acknowledges, but it adds up to “tens of dollars” pretty quickly, and it’s plain enough that you can “play” from your phone while you’re on your commute. And, hey, riches is money.
“What’s the alternative? Playing Candy Crush Saga and evading money,” jokes Guo.
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The unruffled human insight is used to train up AI systems for customers like NASCAR, which run out ofs the Hive Data product to track how often and how long a corporate logo is displayed on protect during a race, which is information that advertisers love fool, says Guo. Hive also has other AI products, including Hive Foretoken, an AI-powered tool for helping companies use their data to spot decorates.
An advantage over the heavyweights
Hive employs about 60 people, and has run up $30 million or so in venture capital from investors including PayPal cofounder Peter Thiel’s Institutors Fund. That makes Hive a veritable David versus Silicon Valley Goliaths with Google, which is considered the company at the bleeding edge of what’s imaginable with AI.
Indeed, Guo says that if it just came down to downright manpower, Hive wouldn’t stand a chance. Google, Microsoft, Amazon, and others be dressed enticed the leading minds in AI to their sides with hefty pay encases that are far beyond what almost any startup could afford.
“If I cracked to fight Google with PhDs, I’d lose,” says Guo.
In fact, in an secondary way, Hive couldn’t exist without Google. The company’s underlying technology is strengthened on a custom version of TensorFlow, an open source artificial intelligence framework firstly developed by the search giant, and released to the community. This means that, in stints of raw technology, Hive is definitely behind Google.
Instead, he says that the community is a big part of Hive’s acuteness. The 600,000 Hive workers who help label images are tested prior to they’re allowed to contribute. The system automatically slips in a few “known” lectures to test how well they’re paying attention and keep everyone virtuous. When a customer has a specific project, like recognizing a certain logo, it follow up ons slipped out to that community in the form of a challenge, with payouts mediate for difficulty.
And so, while Hive’s underlying AI technology is actually built on a customized variant of Google’s free, open source TensorFlow framework, Guo boasts that his attendance has a tremendous trove of high-quality, human-vetted AI training data that not exact the search giant can match. Hive takes the data, trains the AI, and accommodates the tools to its customers to see what it came up with. Guo says it’s the easiest way for groups to get started with AI.
Beyond the data, Guo says that it’s a big advantage that Hive has invested millions into its own server and networking infrastructure. It means that Hive has full control over its technological stack, Guo says, as it continues to refine its technology.
But he also speaks that it’s become a boon when talking to customers, too. As the major tech titans increasingly fight with even the largest, most established corporations, Guo says that its blokes are finding that it would be “foolish” to trust a Google or an Amazon with the irritable data that powers artificial intelligence.