Matias del Campo – författare

Artificial intelligence (AI) applications in architectural design have achieved a critical mass and exploded into the mainstream of architectural imaginations. From practical applications in design and constructionto the implications for architectural theory to a plethora of novel tools for accelerated morphological studies, what has become clear is that the discipline is passing a threshold that fundamentally changes architecture as a whole. However, the most radical change is the interrogation and novel discussion of authorship and agency in design ecologies driven by synthetic imaginations. What does it mean for authorship when more than 50 per cent of the content is generated by a nonhuman player? This issue seems more pressing than ever. In a world that is being transformed by AI on a daily basis, what is the role of the sole genius, and designers, artists and architects? This AD dives deep into current discussions about the human position in architectural design, which is increasingly entangled in an AI-driven design context.

Contributors: Cesare Battelli, Phil Bernstein, Mario Carpo, Benjamin Ennemoser and Ingrid Mayrhofer-Hufnagl, Sarah Fox, Wanyu He, Andrew Kudless, Ryan Vincent Manning, Sandra Manninger, Kyle Steinfeld, Andrew Witt, and Michael Young.

DIFFUSIONS IN ARCHITECTURE A guide to diffusion models and their impact on design, with insight on how this novel artificial intelligence technology may disrupt the industry Diffusions in Architecture: Artificial Intelligence and Image Generators delves into the impact of Generative AI models and their effect on architecture design and aesthetics. The book presents an in-depth analysis of how these new technologies are revolutionizing the field of architecture and changing the way architects approach their work. The architects presented in the book focus on the application of specific AI techniques and tools used in generative design, such as Diffusion models, Dall-E2, Stable Diffusion, and MidJourney. It discusses how these techniques can generate synthetic images that are both realistic and imaginative, creating new possibilities for architectural design and aesthetics. Twenty-two leading designers and theorists offer their insights, providing disciplinary depth by covering the full impact of these learning tools on architecture.

DIFFUSIONS IN ARCHITECTURE

A guide to diffusion models and their impact on design, with insight on how this novel artificial intelligence technology may disrupt the industry

Diffusions in Architecture: Artificial Intelligence and Image Generators delves into the impact of Generative AI models and their effect on architecture design and aesthetics. The book presents an in-depth analysis of how these new technologies are revolutionizing the field of architecture and changing the way architects approach their work. The architects presented in the book focus on the application of specific AI techniques and tools used in generative design, such as Diffusion models, Dall-E2, Stable Diffusion, and MidJourney. It discusses how these techniques can generate synthetic images that are both realistic and imaginative, creating new possibilities for architectural design and aesthetics.

Twenty-two leading designers and theorists offer their insights, providing disciplinary depth by covering the full impact of these learning tools on architecture.

DIFFUSIONS IN ARCHITECTURE

A guide to diffusion models and their impact on design, with insight on how this novel artificial intelligence technology may disrupt the industry

Diffusions in Architecture: Artificial Intelligence and Image Generators delves into the impact of Generative AI models and their effect on architecture design and aesthetics. The book presents an in-depth analysis of how these new technologies are revolutionizing the field of architecture and changing the way architects approach their work. The architects presented in the book focus on the application of specific AI techniques and tools used in generative design, such as Diffusion models, Dall-E2, Stable Diffusion, and MidJourney. It discusses how these techniques can generate synthetic images that are both realistic and imaginative, creating new possibilities for architectural design and aesthetics.

Twenty-two leading designers and theorists offer their insights, providing disciplinary depth by covering the full impact of these learning tools on architecture.

Architecture-specific AI reference combining executable Python code with critical theory Architects and computational designers lack a single resource that integrates AI theory, critical discourse, and working code within an architectural context. The Architects Manual to Artificial Intelligence, written by the co-founders of SPAN, addresses this directly. Covering CNNs, GANs, transformers, diffusion models, and more, the book provides both the conceptual frameworks and executable Python scripts needed to deploy AI in design practice. The manual introduces a distinctive pedagogical system: Grey Boxes catalog architectural applications for specific AI models, while Black Boxes supply executable Python code for tasks such as generating structural details with Pix2Pix, creating 3D terrain with 3DGAN, and optimizing spatial layouts with TransformerGAN. Original frameworks including Vibe Coding, Concatenation, and the AI Iceberg structure the theoretical discourse. The book also covers: Proprietary datasets including the Baroque Plan Dataset of over 2,000 annotated plans used in real project workflowsDetailed analysis of GraphCNN, TransformerGAN, Gaussian Splatting, CycleGAN, and other architectures beyond standard image-generator discourseReal-world project breakdowns from SPAN including the Deep House using StyleGAN2 and the Robot Garden workflowA dual-channel structure enabling simultaneous use as a technical coding workshop and a critical design seminarExamination of how AI reorganizes authorship, form-making, material reasoning, and architectural representation across the built environmentDesigned for advanced architecture students, computational design researchers, practicing architects in technology-forward firms, and studio instructors integrating AI into curricula, this manual occupies the underserved middle ground between purely theoretical texts and general computer science references lacking architectural context.