Artificial Intelligence in Architecture and Interior Design

Design is a creative endeavor that combines logical rationality with intuitive imagination. It operates across divergent and convergent thinking and unfolds in two worlds, namely an internal mental space of perceptual, functional, and conceptual actions, and an external physical space of drawing, copying, and deleting elements. Each physical act aligns the external world with an internal goal. Over the past decade, computational design has undergone a paradigm shift fueled by deep learning. Unlike rule-based parametric systems, models such as GANs, VAEs, and diffusion models learn implicit patterns from extensive architectural datasets, generating solutions that balance creativity and function. Text-to-image diffusion models like Stable Diffusion and DALL-E enable rapid concept visualization and ideation. Concurrently, advances in computer vision and 3D reconstruction, including Neural Radiance Fields (also known as NeRFs), CNNs, and Vision Transformers, are reshaping how architects capture and model built environments. Large language models allow conversational design interaction, expressing intentions in natural language. Collectively, these technologies expand architectural boundaries and foster interdisciplinary collaboration between computer science and architecture. Although this Special Issue focuses on architecture and interior design in the context of AI, its broader aim is to highlight the enrichment of frameworks integrating diverse design practices and artificial intelligence technologies.