New technology is automating the creative process, raising the question of whether algorithms are better painters than humans.
, I was keen to see how well the program worked. After hours of experimentation, it’s clear that DALL-E—while not without shortcomings—is leaps and bounds ahead of existing image generation technology. It raises immediate questions about how these technologies will change how art is made and consumed. It also raises questions about what it means to be creative when DALL-E 2 seems to automate so much of the creative process itself.
Nearly all of them could plausibly pass for professional photographs or drawings. While the algorithm did not quite grasp “Devo hat”—the strange helmets worn by the New Wave band Devo—the headgear in the images it produced came close. In principle, anyone with enough resources and expertise can make a system like this. Google Research recently announced an impressive, similar text-to-image system, and one startup, HuggingFace, is publicly developing their own version that anyone can try right now on the web, although it’s not yet as good as DALL-E or Google’s system.
If these images succeed as art, they are products of how the algorithm was designed, the images it was trained on, and—most importantly—how artists use it. Take Paul McCartney, who came up with the track “Get Back” during a jam session. He didn’t start with a plan for the song; he just started fiddling and experimenting and the band developed it from there.
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