OXIA PALUS

Lebenson gallery and Deeep are proud to show, in collaboration with Morf Gallery, Oxia Palus

George is a UK Space Agency PhD candidate at University College London (UCL) researching trace gases in the Martian atmosphere. George holds a Master’s in Space Science and Engineering from University College London and a Bachelor’s in Mathematics and Physics from the University of Warwick.

George’s journey into the world of AI art is circular, from art to space science to machine learning to art. His influences in AI art lie at the nexus of space exploration, dreams, and science fiction. His work through Oxia Palus, reconstructing the past with AI offers an alternative to how AI is creating new value in the art world. He asks, “If we could use AI to accelerate the identification and reconstruction of all art that has been lost from the world, how would this change our understanding of the history of art and society today?”. 

 Anthony is a Machine Learning and Behavioural Neuroscience PhD candidate at University College London.  Anthony holds a BA in theoretical physics from Trinity College Dublin, an MSc in high performance computing from the University of Edinburgh and an MSc in machine learning from University College London and has worked on many industry projects in the machine learning domain.

With great passion in the machine vision space and the philosophy of computation, Anthony’s interest in AI art is rooted in humankind’s perception of creativity. Since the early 1930s, the mere concept of artificial computation has been at the epicentre of thinking in mathematics and the philosophy of mind. “Are minds mechanical processes?” … and therefore, subject to the same incomplete properties of formal systems as set out by mathematician, Kurt Godel? Humankind’s difficulty in empathising with AI.

 George and Anthony’s different backgrounds, perspectives and motivating passions for art are at the centre of Oxia Palus’ unique approach rooted in an unusual adversarial collaboration, where often competitiveness drives progress. Much like natural selection drives evolution. Often a consensus on the appropriate methods or algorithms cannot be reached and many diverse plans are implemented.