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<p>Acknowledgments xi</p> <p>Contents xii</p> <p>Preface xvi<br /> <i>Lev Manovich</i></p> <p>Prologue xxiv<br /> <i>Matias del Campo</i></p> <p><b>Suppositions 1</b></p> <p>Rice or Pasta? Choose Your AI 2<br /> <i>Mario Carpo</i></p> <p>Taxonomy 6<br /> <i>Matias del Campo</i></p> <p>Diffusions 10<br /> <i>Bart Lootsma</i></p> <p>The Labors of AI 18<br /> <i>Sandra Manninger</i></p> <p>An Artificial Tale 28<br /> <i>Ryan Vincent Manning</i></p> <p>Resistance Is Fertile 38<br /> <i>Joy Knoblauch</i></p> <p>Ontology of Diffusion Models 44<br /> <i>Matias del Campo</i></p> <p><b>Taxonomy</b></p> <p><b>Commorancies</b> <b>55</b></p> <p>The Etiology of a New Collective Architecture 56<br /> <i>Kory Bieg</i></p> <p>Noise, Pixels, and Ancient Metamorphic Rocks 66<br /> <i>Matias del Campo</i></p> <p>Timberpunk, Prompt Odyssey, Synthetic Ground, and Other Projects 78<br /> <i>Soomeen Hahm and Hanjun Kim</i></p> <p>Computation Past Forward 88<br /> <i>Marco Vanucci</i></p> <p>Diffusion Models 98<br /> <i>Alicia Nahmad Vazquez</i></p> <p><b>Vestures 109</b></p> <p>Design as a Latent Condition 110<br /> <i>Daniel Bolojan</i></p> <p>AI, Architecture, and Art 120<br /> <i>Niccolo Casas</i></p> <p>The Advent of Trees in Architecture 13<br /> <i>Daniel Köhler</i></p> <p>Five Points of Architecture and AI 140<br /> <i>Andrew Kudless</i></p> <p>De-Coding Visual Cliches and Verbal Biases 15<br /> <i>Sina Mostafavi and Asma Mehan</i></p> <p>Light Architecture 160<br /> <i>Rasa Navasaityte</i></p> <p>Driftwood Rock 170<br /> <i>Igor Pantic</i></p> <p>Digital Spoliare 180<br /> <i>Dustin White</i></p> <p><b>Estrangements 191</b></p> <p>Imago Mundi Imaginibus Mundi 192<br /> <i>Cesare Battelli</i></p> <p>3D Diffusion or 3D Disfiguration? 202<br /> <i>Immanuel Koh</i></p> <p>Role Play 212<br /> <i>Elena Manferdini</i></p> <p>The Doghouse 222<br /> <i>Sandra Manninger</i></p> <p>Do Humans Dream of Furry Houses? 232<br /> <i>Virginia San Fratello</i></p> <p>Allies in Exile 242<br /> <i>Kyle Steinfeld</i></p> <p><b>Appendix 253</b></p> <p>Epilogue 254</p> <p>Matias del Campo</p> <p>Glossary 256</p> <p>Contributor Profiles 264</p> <p>References 268</p> <p>Bibliography 284</p> <p>Index 286</p> <p>Image Credits 290</p> <p>About the Author 323</p>

<p><b>Matias del Campo </b>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 <i>Neural Architecture - Design and Artificial Intelligence</i> (ORO Editions 2022) and <i>Sublime Bodies</i> (co-authored with Sandra Manninger, Tongji Press 2017)</p> <p><b>Lev Manovich </b>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.</p>

<p> <b>A guide to diffusion models and their impact on design, with insight on how this novel artificial intelligence technology may disrupt the industry</b> <p><i>Diffusions in Architecture: Artificial Intelligence and Image Generators </i>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. <p>Twenty-two leading designers and theorists offer their insights, providing disciplinary depth by covering the full impact of these learning tools on architecture.

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