MoMA Latent Space Painting
- Victor Anferov

- Nov 8
- 1 min read

This project explored the ""latent space"" of an art collection, inspired by Refik Anadol's work at MoMA. We trained a Generative Adversarial Network (GAN) on the public metadata of The Museum of Modern Art's collection, covering over 200 years of art. The AI model learned the stylistic evolution of art history. We then generated ""algorithmic data paintings"" that visualize the machine's ""dreams"" and allusions between different artistic movements. The resulting visuals are abstract, dynamic, and showcase the aesthetic potential of data itself when used as a creative pigment.





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