Shutterstock.AI launches data products for AWS Data Exchange customers
New Shutterstock subsidiary enables businesses of all sizes to train computer vision models at scale.
Shutterstock.AI, a new subsidiary of the widely used creative content platform Shutterstock, has announced the availability of its data on AWS Data Exchange, a service that aims at enabling companies to find and use third-party data in a privacy-compliant way. (That said, Amazon was just hit with a record-high data privacy fine by the EU.)
Other data companies, like Infutor, have also joined the AWS Data Exchange, which was launched in 2019.
The Shutterstock.AI subsidiary was announced earlier this week. It acquired three AI platforms: Pattern89, Datasine and Shotzr. With these AI platforms in place, Shutterstock can commercialize its content library, which includes over 400 million images, videos, 3D models and music files.
Combining these assets with AI allows clients to find and use them intelligently using data, but it also paves the way for advanced visual discovery. A recent comment by Shutterstock CEO Stan Pavlovsky points to the use of this data to “help new customer segments accelerate the development of artificial intelligence, by unlocking the power of data associated with our vast content library.” He mentions autonomous vehicles and content moderation as applications down the road.
Initially, Shutterstock.AI will offer a series of training datasets for AWS customer through the AWS Data Exchange. These datasets apply to multiple industry categories to provide computer vision applications for ecommerce, travel and tourism, self-driving cars and consumer electronics.
Why we care. Data is oil, yes. With the likely deprecation of third-party cookies, and increased privacy regulations (with teeth, apparently), companies are partnering and collaborating to monetize their data and make it available to serve relevant ads and messaging to customers.
In this case, the data on how Shutterstock’s visual assets are used is informing how they can be used in the future by new technology. The data on a picture or video of a traffic light can help a marketer determine if that image will inspire a consumer to buy a product when they see a traffic light in the ad. Or, it can help them connect with only consumers who prefer ads with traffic lights, as opposed to ads with giant blue whales in them. But, that same data could also help a driverless car take a consumer safely to a McDonald’s drive thru.
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