The Lumen Prize celebrates the very best art created with technology through a global competition. We are delighted to announce that two Goldsmiths MA Computational Arts students have been awarded prizes this year.
Eddie Wong won the Lumen Moving Image Award for his work entitled Portrait of the Jungle People. The music for this piece was also created by a Goldsmiths MA Computational Arts alumnus Chris Speed
Portrait of the Jungle People explores both the artist’s family history and the family ‘rhizome’ to honour the offshoots who can neither be traced nor mapped through a series of fragmented narratives and post-memories. The art combines neural networks with language processing models to generate images from text. By combining the predictions of the two models, the artists can use common phrases (prompts) to paint pictures of its underlying concepts, walking through the latent space formed by the training archives’ speculative, fabricated visions.
The work is about how humans and machines make sense of each other, and how this process transitions between co-construction of indigeneity, identity and myth. It emerges from a conflation of machine learning algorithms and postcolonial discourse, presenting the Malaysian-Chinese narrative as fluid and hallucinatory.
«I am delighted to see two of our Goldsmiths MA/MFA Computational Arts students winning the Lumen Prize awards.
The Lumen Prize reflects the best work in Art and Technology today and it is wonderful to see our students recognised for the amazing works they have created»Jesse Wolpert, MA/MFA Computational Arts Programme Lead.
Arjan Emmanuel Sanchez Guerrero won the Lumen Global Majority award for his work entitled Amaroid.
Amaroid inverts the traditional logic of the diorama and that of augmentation. In this project, a virtual-native object gets augmented within and beyond the screen, as an image that travels and transforms across time but also across different materialities, from diegetic reality to non-diegetic reality: an augmented virtuality.
This project is not a paleontology (the study of ancient beings), but a sort of “neontology” (a study of beings to come) of the Latent Space –i.e. the space of lower dimensional representation of what an Artificial Neural Network has learned. It digs into the mechanics of the Latent Space, finding a fossil from a latent world and augmenting its nature. Originally generated by the BigGAN –an AI trained on the contemporary visual world– such fossilization shows a synthetic nature that grows from the remains of an organic one.
Every image generated by the BigGAN is the relief of a mathematical flatness. This project explores and entangles the techniques and the aesthetics of such a process.
If you are interested in studying Computational Arts, check the MA/MFA Computational Arts programmes lead by Jesse Wolpert.