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Computer taught to recognise celebrity faces mistakes Janelle Monáe for Chevy Chase

Machine can correctly name a total of 10,000 stars, but it slipped up when asked to identify a snap of the singer and actress

RESEARCHERS have taught a robot to recognise 10,000 celebrity faces - but it made a hilarious slip-up when asked to identify the singer and actress Janelle Monáe.

A computer firm called Clarifai tested out its star-spotting software on a picture of Monáe, but was shocked when it suggested the snap showed Chevy Chase.

 Can you see it yet? A computer thought these two stars looked a lot like each other
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Can you see it yet? A computer thought these two stars looked a lot like each other

Matthew Zeiler, Clarifai’s CEO and founder, appeared at a tech conference to show off his clever software which uses artificial intelligence to identify faces.

It was shown a picture of Monáe from a post for the film Hidden Figures but thought it was comedy legend Chevy Chase, according to .

"The model is clearly a work in progress," the magazine wrote.

We're not sure whether Janelle (or Chevy) would be flattered by the comparison.

But Peter Andre might be chuffed to know the system thinks he's actually Drake, the Canadian rapper.

We scanned a few British celebs into the system and you can see the results below.

 The software can be used to scan images from the internet, with the name of the person it think is in the snap written in the top right
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The software can be used to scan images from the internet, with the name of the person it think is in the snap written in the top right
 The software thought Geoffrey, star of the much-loved kids show Rainbow, was Welsh actor Rhys Ifans
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The software thought Geoffrey, star of the much-loved kids show Rainbow, was Welsh actor Rhys Ifans
 Ainsley Harriot was likened to basketball player Magic Johnson
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Ainsley Harriot was likened to basketball player Magic Johnson
 It did a better job of recognising Katie Price
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It did a better job of recognising Katie Price

"Recognising faces is a common artificial-intelligence task, but recognising who, specifically, is in an image can be much trickier, especially in different lighting conditions or when the subjects are not staring straight at a camera or are occluded by other people or objects," an expert from MIT Technology review added.

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