Jeyun J Cloud
United States
Where do you locate yourself in relation to the systems you work with?
Where are you heading, and what is pulling you there?
How would you describe the space your practice is currently unfolding in?
Artist Statement
Description
Are We Gazing at the Same Moon? Do we observe things within the same time and space? In astronomical photography, the Lunar Mosaic technique is used to construct high-resolution images of the moon by collaging captured parts, each taken at different times. This project is an artistic experiment built upon a moon image captured by NASA’s Galileo spacecraft in 1992. However, the artwork employs generative AI to expand the known boundaries of each fragments, imagining each one coming from different planets and revealing the unseen portions. By showcasing the parallel existences and possibilities of the moon, it constructs a surreal picture, re-imagining the moon as a discontinued collection of moons This artwork establishes a ritual of moon-gazing, presenting a massive image of the moon composed of multiple stitched-together fragments. As the camera gradually zooms out, the spaces beyond each fragment are slowly revealed—not as part of the same origin, but as different imaginary moons. Ascending through collage of moons, the world fractures into multiple concurrent timelines, scattering and reuniting in an endless cycle of divergence and convergence. "One thousand people, one thousand moons"—where the boundary between individual emotions and collective memory dissolves into a shared, shifting reflection.
Process
The moon has long been a symbol of collective human experience, appearing in art, literature, and philosophy as a means to explore time, space, and memory. Its familiar presence in the night sky connects people across distances, eras, and cultures, serving as a shared point of reference for thoughts, emotions, and reflections. Yet, how much of our experience of the moon is truly shared? What if, despite our collective memory of it, the act of gazing at the moon is more fragmented and subjective than we realize? This project is a research experiment about multiplicity and deconstruction in the age of AI. Focusing on the process of divergence and convergence, it reflects the dual-possibility nature of generative technologies, raising profound questions about the relationship between parts and the whole, and the connection between personal and collective memory. In a time marked by nationalism, regional conflicts, and global divergence, the project’s theme of dispersal and reassembly is poignant. By translating the segmented Moon artwork across different cultural boundaries, it reminds us that we share the same cosmic vantage point - even when our daily realities seem fractured. The piece ultimately reflects both the fragmentation of the modern world and the ongoing potential for reassembly and common ground.
Tools
Concept and Technique: Concurrent Reality This work is part of the "Concurrentix" art experiments and avoids aiming for realistic depiction. Instead, it delves into the concept of Concurrent Reality, using generative AI to showcase the dislocated nature of our collective memory and experience of the moon. In this context, the moon becomes a metaphor for human experience - seemingly unified, yet ultimately disjointed and subjective. Inspired by the Lunar Mosaic technique (used in astronomical photography to collage moon fragments captured at different times), this project operates in reverse. Built upon an archival moon image, the artwork employs generative AI’s out-painting capability to expand the boundaries of each fragment, imagining them coming from different planetary sources and revealing their unseen portions. The work applies two key techniques to achieve this: 1. Spatial Dislocation: Breaking down the original moon figure into discontinuous fragments and utilizing AI out-painting to expand unique, imaginary moon terrains for each segment. 2. Temporal Dislocation: Subdividing the linear movie sequence of a dynamic moon journey into multiple timelines by creating several Image-to-Video generations simultaneously from different start and end frames.





