AI into the canonic design process: Diffusion models in architecture and their impact in the creativity workflow

In the world of architecture, technological advancement has always led to major changes in the profession. Until a few decades ago, design was done by hand, whereas today we make use of complex software that supports us throughout all the design phases. Today we are entering the age of AI and our aim with this thesis is to test how this can influence the canonical creative process. The thesis therefore aims to integrate the use of tools based on generative AI, with a specific focus on Diffusion Models. The work therefore interrogates the design process: how it can be shortened to achieve high efficiency or how it can be radically reimagined to become more effective. This was also explored through interviews with professionals from MVRDV and UNStudio that led us to define some key concepts applicable that were then applied to two practical exercises.