![]() ![]() The images here are from my wall of Caffeinated Diversions, fifty of the most interesting results from these morning experiments. It is a wondrous interaction, and there is a magical space where I can draw very stylized or abstracted figures and the neural network infers some very interesting anatomical results, always beautifully lit and shaded. Then, once trained, I can use it to dynamically ‘paint’ my drawings in the style of my photography. The idea behind this “AI tool” is that I train it to learn the correspondence between my drawing style and photographic representations of the human figure, in this case photography carefully lit and shot by me in the studio. ![]() Over the last couple years I have been using part of my morning drawing time (yes, with a coffee… or two, or three), to create input drawings to test my Bodies neural network, which I trained on a portion of my BodiesinMotion.photo library. People who know me know that drawing in essential to my creative process. It was great to chat ML, tech and art with a group of super-smart computer scientists, engineers, and thinkers.Ĭaffeinated Diversions, 50x archival prints, 21x15cm Even though they’re unfinished, they were important developmental milestones and each succeeded/failed in interesting, instructive ways. I’ll try to start uploading more of these here in the coming months. I’ve been sharing some of the work here, but mostly finished pieces, so it was nice to dust off some of my earlier, formative experiments from the recesses of my hard drive. ![]() The talk reviewed the last three years of my artistic experimentation using machine learning (AI) as a creative tool for art making and showcased an eclectic range of successes and failures. I’m just back from a trip to Oxford where I gave an afternoon seminar on my explorations with art and machine learning to an amazing group of researchers and distinguished professors at Oxford University. ![]()
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