Counting Craters on the Moon, 2019

DUAL-CHANNEL VIDEO ● DEEPMOON DATASET ● ARCHIVAL MATERIAL ● CNC MARBLE SCULPTURE ● DIGITAL PRINT ON TEXTILE ● MULTIMEDIA INSTALLATION ● DRAWINGS
01
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
project image
/23
01
/23

Edition of 3 + 2AP.

video + portfolio request to contact@kyriakigoni.com

As a result of advances in machine learning, our understanding of today's world is ever more mediated by machines. What challenges does deep learning bring to human-based knowledge? What do machines see and do differently than humans? How can artificial intelligence enhance new forms of experience and understanding?

To address these questions, in Counting Craters on the Moon, Kyriaki Goni purposely turns her gaze to a distant and uncanny territory: the Moon and its surface. The Moon, according to the artist, constitutes a fascinating example and offers an interesting analogy. Lacking an atmosphere, it operates as a data center which stores in its body the memory of our solar system and allows predictions for the future.

The installation presents an imaginary encounter between astronomer Johann Friedrich Julius Schmidt (1825-1884) and the neural network DeepMoon, both of which set out to count the craters on the moon. Speculating upon the possible synergies between human and machine, the artist invites us to imagine how we can learn from and with machines in order to build different, multiple and, possibly, collective understandings of the surrounding world and its cosmos.

In August 2019, Goni asked the DeepMoon team to run the algorithm on Schmidt’s map. The network detected a few craters, although it performed exactly what it was expected to, namely, to trace the color gradient. The algorithmic eye failed to recognise the result of the meticulous and persistent human observation, as well as the complex shapes and tones the human eye perceived and reproduced in high detail. According to Mohamad Ali-Dib from the DeepMoon team, the answer to what any neural network is seeing is often not trivial and this result demonstrates the limitation of the neural network.

HUMANITIES AND ARTIFICIAL INTELLIGENCE EUROPEAN COMMISSION

CURATORIAL TEXT BY DAPHNE DRAGONA

SOLO SHOW AT DRUGO MORE, 2020 CURATED BY THE ARTIST

SOLO SHOW AT AKSIOMA, 2019 CURATATED BY DAPHNE DRAGONA

Η ΑΛΛΗΛΕΠΙΔΡΑΣΗ ΑΝΘΡΩΠΟΥ - ΥΠΟΛΟΓΙΣΤΗ ΜΕΣΑ ΑΠΟ ΤΗΝ ΤΕΧΝΗ ΣΥΝΕΝΤΕΥΞΗ

THE WORK WAS PRODUCED BY AKSIOMA.