The Replicator: Maybe You Can Have Everything
Project information
submitted by
Funda Zeynep Aygüler
Co-Authors
Mina Boylu, Hikmet Arin Aydın, Kai-Ting Chang, Lucas Garancher, Dania Gonzalez Sanabria, Alina Boes, Agustin Cifuentes, Melek Sungur, Ezequiel Ader
Mentors
Funda Zeynep Aygüler, Prof. Martin Hesselmeier
Faculty:
Architecture and Urbanism,
Art and Design,
Media,
Bauhaus.Module
Degree programme:
Architecture (Bachelor of Science (B.Sc.)),
Architecture (Master of Science (M.Sc.)),
MediaArchitecture (Master of Science (M.Sc.)),
Public Art and New Artistic Strategies (english) (Master of Fine Arts (M.F.A.)),
Productdesign (Master of Arts (M.A.)),
Media Art and Design (Bachelor of Fine Arts (B.F.A.)),
Media Art and Design - Study programme Integrated International Media Art and Design Studies (IIMDS) (Master of Fine Arts (M.F.A.) and Master of Arts (M.A.))
Type of project presentation
Exhibition
Semester
Summer semester 2024
- Marienstraße 5
- Bauhausstraße 9a - Digital Bauhaus Lab
Available during summaery opening hours
Participation in the Bauhaus.Modules
Project description
In Star Trek, the replicator is a device capable of creating and recycling objects—from simple meals to intricate non-food items—by assembling them from atomic patterns. Such capabilities, which meet all material needs from food to everyday objects, envision a world where the value of individual items diminishes, leading to a society with obsolete monetary systems and expanded leisure time. This post-scarcity scenario, where every physical need is just a command away, also raises philosophical questions about the nature of 'replicated' versus 'real'.
Drawing inspiration from the replicator, this exhibition presents a series of works that bridge the gap between generative artificial intelligence and material creation. The works emerge from a semester-long investigation into the open-ended and indeterminate future of generative AI applications in physical production. The exhibition features 3D-printed objects and a hologram created using generative AI tools. The works highlight the limitations and complexities of this technology, murky interfaces, and the unpredictable nature of physical production through AI.