Diffusions in Architecture: Artificial Intelligence and Image Generators -

Diffusions in Architecture: Artificial Intelligence and Image Generators

Matias del Campo (Herausgeber)

Buch | Softcover
352 Seiten
2024
John Wiley & Sons Inc (Verlag)
978-1-394-19177-2 (ISBN)
47,35 inkl. MwSt
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.

Matias del Campo is a registered architect, designer, and educator. He is an Associate Professor at Taubman College of Architecture and Urban Planning, University of Michigan, director of AR2 IL – The Architecture and Artificial Intelligence Laboratory at UoM, and an affiliate faculty member of Michigan Robotics and Data Science. Matias del Campo is the co-founder of the architecture practice SPAN. His previous publications include Neural Architecture - Design and Artificial Intelligence (ORO Editions 2022) and Sublime Bodies (co-authored with Sandra Manninger, Tongji Press 2017) Lev Manovich is a Presidential Professor at The Graduate Center, City University of New York, and the founder and director of the Cultural Analytics Lab. He is an artist, writer, and one of the most influential theorists of digital culture worldwide.

Acknowledgments xi

Contents xii

Preface xvi
Lev Manovich

Prologue xxiv
Matias del Campo

Suppositions 1

Rice or Pasta? Choose Your AI 2
Mario Carpo

Taxonomy 6
Matias del Campo

Diffusions 10
Bart Lootsma

The Labors of AI 18
Sandra Manninger

An Artificial Tale 28
Ryan Vincent Manning

Resistance Is Fertile 38
Joy Knoblauch

Ontology of Diffusion Models 44
Matias del Campo

Taxonomy

Commorancies 55

The Etiology of a New Collective Architecture 56
Kory Bieg

Noise, Pixels, and Ancient Metamorphic Rocks 66
Matias del Campo

Timberpunk, Prompt Odyssey, Synthetic Ground, and Other Projects 78
Soomeen Hahm and Hanjun Kim

Computation Past Forward 88
Marco Vanucci

Diffusion Models 98
Alicia Nahmad Vazquez

Vestures 109

Design as a Latent Condition 110
Daniel Bolojan

AI, Architecture, and Art 120
Niccolo Casas

The Advent of Trees in Architecture 13
Daniel Köhler

Five Points of Architecture and AI 140
Andrew Kudless

De-Coding Visual Cliches and Verbal Biases 15
Sina Mostafavi and Asma Mehan

Light Architecture 160
Rasa Navasaityte

Driftwood Rock 170
Igor Pantic

Digital Spoliare 180
Dustin White

Estrangements 191

Imago Mundi Imaginibus Mundi 192
Cesare Battelli

3D Diffusion or 3D Disfiguration? 202
Immanuel Koh

Role Play 212
Elena Manferdini

The Doghouse 222
Sandra Manninger

Do Humans Dream of Furry Houses? 232
Virginia San Fratello

Allies in Exile 242
Kyle Steinfeld

Appendix 253

Epilogue 254

Matias del Campo

Glossary 256

Contributor Profiles 264

References 268

Bibliography 284

Index 286

Image Credits 290

About the Author 323

Erscheinungsdatum
Vorwort Lev Manovich
Verlagsort New York
Sprache englisch
Maße 213 x 274 mm
Gewicht 1066 g
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik Architektur
ISBN-10 1-394-19177-4 / 1394191774
ISBN-13 978-1-394-19177-2 / 9781394191772
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
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