C O D E
C H R O N I C L E S
bitforms gallery is pleased to host a closing reception for "Code Chronicles" Tuesday, April 11, between 4 - 7 PM. The exhibit will remain on view through Saturday, April 15.
All works in "Code Chronicles" will be on view, and the reception will highlight contributions to Ana María Caballero's collaborative poem "Things We Are Saving To Write". The collaborative poem will be offered as an open edition after the exhibition closes.
"Code Chronicles" examines how generative systems mediate continuity with artworks from eight pioneering artists: Ana María Caballero, Sarah Friend, LIA, Sara Ludy, Maya Man, Sarah Ridgley, Helena Sarin, and Ivona Tau. Exhibited works riff on interdisciplinary themes of perception, impermanence, obscurity, and memory, plotting a collection of points whose coordinates satisfy a given relation to one another. "Code Chronicles" is curated by Aleksandra Artamonovskaja, a creative producer whose work explores manifestations of digital identities and the role of art in the digital future.
The internet began as a collection of networks, and matured into a tool for personal expression. Now in its third iteration, web3 intends to allow users to carry information across discrete platforms and form a unified identity based on their interactions. Likewise, progressive art forms engaged with blockchain technology encourage audiences to co-create with artists through parameters encoded into artistic media. These artist-collector relationships occasionally supplement generative systems based on a minter’s timezone, latitude, wallet address, or other objective datapoint.
In part, "Code Chronicles" focuses attention on chance iterations enabled by generative processes. Although AI and generative practices are both forms of computational art, generative art dates to the mid-twentieth century, while AI has emerged by leveraging advancements in machine learning. Since generative art typically relies on mathematical algorithms or rule-based systems, it tends to offer artists more control over the outcome and provides a determined aesthetic. Artificial intelligence, however, learns patterns in a given dataset to render imagery. The fidelity of AI outputs are determined by a recursive combination of created or found image-data, and artistic instruction.