1 minute reading time (234 words)

Helena Sarin: Why Bigger Isn’t Always Better With GANs And AI Art

Untitled2 Detail from Improvisation 30 (Cannons), Wassily Kandinsky, 1913
AI art using GANs (generative adversarial networks) is new enough that the art world does not understand it well enough to evaluate it. We saw this unfold last month when the French artists' collective Obvious stumbled into selling their very first AI artwork for $450K at Christie's.

Many in the AI art community took issue with Christie's selecting Obvious because they felt there are so many other artists who have been working far longer in the medium and who are more technically and artistically accomplished, artists who have given back to the community and helped to expand the genre. Artists like Helena Sarin.

Sarin was born in Moscow and went to college for computer science at Moscow Civil Engineering University. She lived in Israel for several years and then settled in the US. While she has always worked in tech, she has moonlighted in the applied arts like fashion and food styling. She has played with marrying her interests in programming and art in the past, even taking a Processing class with Casey Reas, Processing felt a little too much like her day job as a developer. Then two years ago, she landed a gig with a transportation company doing deep learning for object recognition. She used CycleGAN to generate synthetic data sets for her client. Then a light went off and she decided to train CycleGAN with her own photography and artwork.

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