Upon the release, the social media users are all over the new Microsoft application called How-Old.net. The new learning application uses face detection software to determine the age and gender. But more often than not, the app was completely off when guessing people’s ages. Microsoft explains that they are still improving the feature.

My daughter Nathalie tried the Microsoft’s How-Old.net. She just took a picture of herself and the app uses a facial recognition software and machine learning to guess her age. It seems like she is enjoying it, despite an inconsistent results pattern. She just simply prepares herself to be devastated or flattered with the new app.

How Old.Net

One of the biggest viral sensations so far this year has been the face recognition site How-old.net.

According to reports, Microsoft is keeping the details of exactly how the software works under wraps, but it leverages the power of existing facial-recognition technology and machine learning that uses the data it amasses to improve performance.

Meanwhile, this is what you agree to by uploading your photo to How Old.net: “Microsoft does not claim ownership of any materials you provide to Microsoft (including feedback and suggestions) or post, upload, input, or submit to any Website Services for review by the general public, or by the members of any public or private community.

However, by posting, uploading, inputting, providing, or submitting your Submission, you are granting Microsoft, its affiliated companies, and necessary sublicensees permission to use your Submission in connection with the operation of their internet business (including, without limitation, all Microsoft services) the license rights to copy, distribute, transmit, publicly display, publicly perform, reproduce, edit, translate, and reformat your Submission to publish your name in connection with your Submission, and to sublicense such rights to any supplier of the Website Services”.

According to an article published in Science in February said that DeepFace is now “as accurate as a human being at a few constrained facial recognition tasks”.

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