Category: ai art research
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Transfer Learning
This print illustrates the process of transfer learning, a machine learning technique when a model trained on one task is reused –usually to save time and computing energy– for another related task. A series of uncanny images reveals a machine learning model’s transition from a training dataset to a primary one.
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Tiny Datasets
The intimacy of a tiny dataset approach is in contrast with big data and its tendency to produce homogenized results; the Tiny Dataset series celebrates its local, limited, situated, chaotic, and precise results in alliance with Donna Haraway’s critique of “The God Trick.”
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Five Guide Rails for Artists Working with Machines and A.I.
While attending the July Center for Machine Arts residency, surrounded by so many seductive artmaking technologies, I had to spend my time efficiently as we prepared for a fast-approaching exhibition. This is not an unfamiliar process for me as I routinely evaluate how machine learning serves my art practice; sometimes it does and other time…
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Summer Art + AI Outreach Programs
This week with the help of my nephew Ramsey Karson, we hosted numerous Art + AI outreach programs in the University of Vermont FabLab. The program builds from the Athena Dataset, integrates P5 programming and an introduction to our genetic algorithm. We worked with UVM Extension and Vermont 4H and the UVM Upward Bound Program.…