Stas Bartnikas x Obvious work coming to Chicago exhibition until Mar. 19
Doomsd-AI Clock displayed in Chicago Human/Nature exhibit
The collaboration between Stas and the French AI-Art collective is coming to a non-commercial gallery in Chicago for two months. The Weinberg/Newton Gallery, dedicated to promoting social justice causes, is partnering with the Bulletin of the Atomic Scientists to present Human/Nature, addressing the urgent issue of climate change. The gallery is located at 688 N. Milwaukee Ave, and the exhibition is only running for two months, from Jan. 14 to Mar. 19 2022.
The exposition we have coming to the gallery is the Doomsday Clock. Together Stas and Obvious created several fascinating AI-generated landscapes of Iceland; it gives us a chance to consider the most significant challenges facing humanity and the urgency in solving them. They chose the best to represent our impact on Mother Earth out of these images. The unique part of this experiment is the energy-filled landscape art that AI could produce. It truly expresses the beauty, power, and amazement of Earth. The perfect chance to explore the conversation about how fragile the Earth is.
About Doomsday
The original Doomsday Clock, famously presented by a group of scientists concerned about humanity's impact on our planet, gave creation to the idea that we were just “minutes from midnight” on the convergence of extinction. Project Doomsday was created when Stas presented thousands of his aerial photographs to the Obvious AI engine. Together, Stas and Obvious chose a small number of the brilliant images produced by the machine to showcase our impact on the world and our proximity to irreversible changes.
Who is Obvious
Obvious, a French AI-Art Collective uses machine learning to program its computers to create thoughtful art pieces. It gives an insightful perspective into the “eye” of the machine. It allows us to see what a machine “sees” when analyzing thousands of art pieces. With the sharp lens of Stas, they created Doomsday to bring attention to the role of AI and machine learning in challenging irreversible climate change.