NTAA22 FINALIST: Egor Kraft - Content Aware Studies Series
Content Aware Studies is a series of artistic investigations that spans computational, sculptural, screen-based and textual works that examine what artistic, technical and philosophical capacities machine learning technologies hold, both as means for automatic historical investigation and synthetic knowledge production.
The process, developed for over a year now in collaboration with data scientists engaged in training artificial neural networks, directed to replenish lost fragments of sculptures and friezes of classical antiquity and generate never before existing, yet authentic objects of that era. The research examines how a number of advanced AIs: specifically modified General Adversarial Networks particularly known as recent advancements in computer vision, cognition and image rendering operate when trained on datasets consisting of thousands of 3D scans of classical sculptures from renowned international museum collections. The algorithm generates models, which are then 3D printed and CNC routed in marble and synthetic materials, filling the voids in the damaged marble sculptures.