bytefeed

Slumdog Billionaires: AI Artist Reimagines How World's Wealthiest Would Look If Poor - Credit: Indian Express

Slumdog Billionaires: AI Artist Reimagines How World’s Wealthiest Would Look If Poor

In a world where the gap between the rich and poor continues to widen, an AI artist has used his work to bridge that divide. Mario Klingemann, a German-based AI artist, recently created a series of portraits featuring some of the world’s wealthiest people in poverty-stricken settings.

Klingemann used generative adversarial networks (GANs) to create these images by training them on thousands of photographs from slums around the world. He then applied this data to photos of billionaires like Bill Gates and Jeff Bezos, transforming their faces into those of impoverished individuals living in extreme conditions. The result is both thought-provoking and heartbreaking as it highlights how drastically different life would be for these wealthy individuals if they were born into poverty instead.

The project was inspired by Klingemann’s own experience growing up in East Germany during its communist era when he saw firsthand what it meant to live without basic necessities such as food or shelter. Through his art, he hopes to bring attention to global inequality while also encouraging viewers to think about how much privilege they have access too simply because of their birthright or social status.

This isn’t the first time Klingemann has used GANs for creative purposes; he previously created works that blended classic paintings with modern photography as well as manipulated celebrity faces using facial recognition technology. His latest project serves not only as an eye opener but also a reminder that we all have something valuable we can contribute towards making our society more equitable for everyone regardless of background or wealth level.

|Slumdog Billionaires: AI Artist Reimagines How World’s Wealthiest Would Look If Poor|Social Issues|Indian Express

Original source article rewritten by our AI: Indian Express

Share

Related

bytefeed

By clicking “Accept”, you agree to the use of cookies on your device in accordance with our Privacy and Cookie policies