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Back in October 2017, Google announced Clips, a device that housed a camera that would capture the moments of your life. Using artificial intelligence, the camera would snap random pictures throughout the day, all without a user's input.
Some people might think that this is all done by a fancy algorithm – and, for the most part, they’d be correct in that assumption. But Google also revealed something really interesting about the Clips product.
Namely, Clips was trained in photography by professionals.
That’s right – the AI-powered camera uses what Google calls “human-centered machine learning,” which sounds terrifying until you learn what that means in practice.
Image of Google Clips via Google.
The whole purpose behind the Clips gadget was so that people could enjoy their life without having to worry about taking photos of it.
Part of doing this is having a camera that not only can take its own pictures, but also can decide which shots are worthy of keeping and which need to be thrown away.
In breathless marketing, Google describes the target audience:
“This year, people will take about a trillion photos, and for many of us, that means a digital photo gallery filled with images that we won’t actually look at…This is especially true with new parents, whose day-to-day experience is full of firsts. During moments that can feel precious and fleeting, users are drawn to their smartphone cameras in hopes of capturing and preserving memories for their future selves. As a result, they often end up viewing the world through a tiny screen instead of interacting using all their senses.”
Google put out job listings for photographers and got a photojournalist, documentary photographer, and a fine arts photographer to join the project. The three people were tasked with answering one simple question, “What makes a memorable moment?”
To begin, the Google team trained the AI to recognize bad photos along criteria established by the group in tandem with the photographers. Then the team further refined the AI to things like composition, reading behavioral patterns of subjects in the picture (such as greetings), and self-selection of captured photos.
Kehl is our staff photography news writer since 2017 and has over a decade of experience in online media and publishing and you can get to know him better here and follow him on Insta.
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