UVM Art + Artificial Intelligence (AI) Research Group

UVM Art + Artificial Intelligence (AI) Research Group

The Art + Artificial Intelligence (AI) Research Group at UVM
employs machine learning to investigate new approaches to artistic image production. More broadly, the project explores emerging artistic practices with Machine Learning and AI while referencing an artistic lineage to artists such as Wassily Kandinsky, Jonn Cage and Yoko Ono. These artists employed instructions and systems in their non-digital artworks. For example, Kandinsky developed a science of aesthetics with the basic elements of point, line and plane; Cage used the oracle ‘I Ching’ like a computer to inform his compositional decisions; Ono wrote poetic scores that turn her audience into active participants when they follow a series of imaginative instructions. Inspired by these artists and curious about the potential for human + machine collaboration, our work emerges through growth-mutation-evolution lifecycles; our human-machine alliances expose a dynamic relationship between creation and destruction.

Emergence is the premier project of the Art + AI Research Group at the University of Vermont. In this project we cultivate artworks that evolve over generations. The resulting images emerge from both human and machine interference and express the peculiar human experience with architectures of order, power and chaos. The public is invited to participate in the project through generative art performances that take place in virtual and gallery settings.

The original dataset for Emergence includes  Dancing Stars.

If you are interested in one of our current programming internships you can see our genetic algorithm in action about halfway through this talk we gave at the Vermont Studio Center in December 2020. 

Read this article about us by Helen Hill

UVM Art and AI Instagram feed

UVM Art and AI page on Facebook

krYshe not1R-us, 2020.

View more artifacts.

The Team:
Jenn Karson, lecturer Department of Art and Art History, University of Vermont
Kerime Toksu, Vermont Advanced Computing Core, University of Vermont

Ethan Davis, M.S. Data Science ‘21
Sarah Pell, M.S. Computer Science ‘20

Syd Culbert. B.A. Computer Science and Studio Art ’23
Anna Hulse, B.S. Natural Resources, Political Science, Studio Art minor ’21
Emma Garvey, B.S. Mechanical Engineering ’19
Fred Sanford, B.S. Mechanical Engineering ‘20
Yifeng Wei, B.A. Studio Art ’19,  M.F.A Parsons School of Design ’21

Funding and Support:
Department of Art and Art History, UVM
Vermont Advanced Computing Core, UVM
Coor Collaborative Fellowship, Humanities Center, UVM
CatCoders funding from Department of Computer Science, UVM Spring 2020
Northeast Cyberteam/NSF funding, Summer 2020
This work was supported in part by the National Science Foundation (NSF) under award No. OAC-1659377.
Computations were performed on the Vermont Advanced Computing Core supported in part by National Science Foundation (NSF) award No. OAC-1827314.