Let me make it clear regarding how Tinder creates better matches through AWS
Dating application is utilizing the cloud merchant’s image recognition technology to higher categorise and match users

Popular dating app Tinder is making use of image recognition technology from Amazon Web Services (AWS) to power its matching algorithm for premium users.
Talking during AWS re:Invent in December, Tom Jacques, vice president of engineering at Tinder explained just just just exactly how it really is with the deep learning-powered AWS Rekognition solution to determine user’s key faculties by mining the 10 billion pictures they upload daily.
“The challenges we face are in understanding who people want to see, whom they match with, that will talk, exactly just just what content can we demonstrate and exactly how do we best present it to you,” Jacques outlined.
Tinder ingests 40TBs of information a time into its analytics and ml systems to energy matches, that are underpinned by aws cloud solutions.
Jacques claims that Tinder understands from the data that the main motorist for whom you match is pictures. “we come across it when you look at the information: the greater amount of images you have got, the larger odds of success to complement.”
whenever a user joins Tinder they typically post a collection of pictures of by themselves and a quick written bio, but Jacques claims a growing wide range of users are foregoing the bio completely, meaning Tinder had a need to find a method to mine those pictures for information that may power its tips.
Rekognition enables Tinder to tag these billions automatically of pictures with character markers, like an individual by having an electric guitar as being a musician or ‘creative’, or somebody in climbing gear as ‘adventurous’ or ‘outdoorsy’.
Tinder makes use of these tags to enrich their individual pages, alongside structured information such as for example training and work information, and unstructured natural text information.
Then, beneath the covers, Tinder “extracts all this information and feed it into our features shop, which will be an unified solution that permits us to manage on line, streaming and batch processing. Read more