All YIN No YANG

Artistic proposal that seeks to build a dialogue between contemporary machine learning methods for image generation and the process of individuation, understood here as articulating the becoming of form.

We explore the varieties of formal divergence made possible using text-to-image diffusion models, probing the efficacy of using semantic description as a constraint to parameterise aesthetic variation within an original dataset of oil paintings. Ongoing collaboration with Iulia Ionescu and Murad Khan, as a moving image and performative experiment.