What We Did With A GAN To Create Your AI-Generated Lover

BuzzFeed is all about exploring new ideas for content, no matter how outside the box. Last December, BuzzFeed CEO Jonah Peretti posted an ambitious idea into the company’s Slack (paraphrased):

It could be fun to create a quiz called ‘Who’s Your Future Partner?’ where the BuzzFeed user inputs what they want in a partner, and the result is the image of a fake person with the caption ‘Congrats, hope you have a great life together!’

Always up for a challenge, a number of BuzzFeed writers, engineers, and myself (as a data scientist) decided to experiment if this more advanced quiz format was feasible. It felt like an opportunity to learn something new and create an even more engaging experience for our audience.

A GAN, a generative adversarial network, is nowadays the most popular way to generate believable fake images. I won’t go into detail on how GANs work as there are many, many other articles that do it better, but the tl;dr is that they are a neural network architecture that simultaneously trains both a fake image generator and a discriminator to tell real input images from fakes ones. As the GAN trains, fake images become progressively more “real” over time. We can then use the generator to create fake images for fun!

The process isn’t perfect though. GANs can occasionally go off the rails and include hilarious artifacts. The Twitter account Normal Cat Pics is a good novelty account illustrating generated cats from a GAN trained on cats:

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