Swiss dating app startup Blinq is playing around with a little algorithmic hot or not catnip, with a plan to add a machine-learning powered attractiveness assessment feature to help its users pick the photos that show them at their best.

In the meanwhile, it’s launched the feature as a standalone website, called, to test how much appetite there is for robotically judged hotness. (The website launched last week and, inevitably, after two days had racked up more than two million unique visits, so it’s not hard to see why they’re ploughing this click-festy furrow…)

“We are going to integrate the algorithm in theBlinq app,” co-founder Jan Berchtold tells TechCrunch. “The users will have the possibility to upload several images before they set up their account. By doing so they can test which of them will probably perform better.”

The tech powering the algorithm was developed by third year PhD student Rasmus Rothe, of theComputer Vision Lab at ETH Zurich, including using image data and attractiveness ratings supplied by Bling — the latter gleaned from the binary ‘hi or bye’ choices Blinq users make as they swipe through potential matches.

“We used more than 100,000 images and more than 20 million ratings between users from our data base,” says Berchtold, explaining the role the app’s data played in the algorithm’s aesthetic training.

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