Augmented (mate)reality: Exploring Hybrid Materials From Machine Learning To Physical Production

While cities face daily challenges from emerging climate patterns, there is a need to rethink how we live and build our urban environments with a new agenda. Existing city networks are filled with obsolete buildings whose structures and materials require replacement, adaptation, or reinforcement. Biomaterials, which have emerged over the last decades, offer an exciting opportunity while questioning the lifespan of materials and the need for temporary constructs. Although significant research has been conducted, the main issue of scaling remains. Whether used as a growing material on a traditional substrate, as an autonomous bio-membrane, or as a structure attached to existing infrastructure, it is crucial to explore advanced techniques for amalgamating living and non-living matter and integrating past and post-fabrication processes. This paper presents work produced within the framework of an undergraduate design studio focused on applying hybrid materials for sustainable, data-driven design, inspired by machine learning (ML) text-to-image datasets.