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Künstliche Intelligenz (KI) hat Eingang in unzählige Branchen gefunden. In der Architektur steckt der Einsatz von KI noch in den Kinderschuhen, doch die Entwicklung der letzten Jahre hat vielversprechende Ergebnisse gebracht. Das Buch ist eine gut verständliche Einführung. Sie bietet einen Überblick über die Geschichte der KI und ihre ersten Anwendungen in der Architektur. Im zweiten Teil präsentiert der Autor konkrete Beispiele für den kreativen Einsatz von KI in der Praxis. Führende Experten, von der Havard-University bis zur Bauhaus Universität, eröffnen schließlich in Essays vielfältige Perspektiven auf das Potenzial von KI. Als Einführung zeigt das Buch ein Panorama dieser neuen technologischen Möglichkeiten und verdeutlicht so das Versprechen, das sie für die Architektur darstellen.
Artificial intelligence is everywhere – from the apps on our phones to the algorithms of search engines. Without us noticing, the AI revolution has arrived. But what does this mean for the world of design? The first volume in a two-book series, Architecture in the Age of Artificial Intelligence introduces AI for designers and considers its positive potential for the future of architecture and design. Explaining what AI is and how it works, the book examines how different manifestations of AI will impact the discipline and profession of architecture. Highlighting current case-studies as well as near-future applications, it shows how AI is already being used as a powerful design tool, and how AI-driven information systems will soon transform the design of buildings and cities. Far-sighted, provocative and challenging, yet rooted in careful research and cautious speculation, this book, written by architect and theorist Neil Leach, is a must-read for all architects and designers – including students of architecture and all design professionals interested in keeping their practice at the cutting edge of technology.
Providing the most comprehensive source available, this book surveys the state of the art in artificial intelligence (AI) as it relates to architecture. This book is organized in four parts: theoretical foundations, tools and techniques, AI in research, and AI in architectural practice. It provides a framework for the issues surrounding AI and offers a variety of perspectives. It contains 24 consistently illustrated contributions examining seminal work on AI from around the world, including the United States, Europe, and Asia. It articulates current theoretical and practical methods, offers critical views on tools and techniques, and suggests future directions for meaningful uses of AI technology. Architects and educators who are concerned with the advent of AI and its ramifications for the design industry will find this book an essential reference.
Architects who engaged with cybernetics, artificial intelligence, and other technologies poured the foundation for digital interactivity. In Architectural Intelligence, Molly Wright Steenson explores the work of four architects in the 1960s and 1970s who incorporated elements of interactivity into their work. Christopher Alexander, Richard Saul Wurman, Cedric Price, and Nicholas Negroponte and the MIT Architecture Machine Group all incorporated technologies—including cybernetics and artificial intelligence—into their work and influenced digital design practices from the late 1980s to the present day. Alexander, long before his famous 1977 book A Pattern Language, used computation and structure to visualize design problems; Wurman popularized the notion of “information architecture”; Price designed some of the first intelligent buildings; and Negroponte experimented with the ways people experience artificial intelligence, even at architectural scale. Steenson investigates how these architects pushed the boundaries of architecture—and how their technological experiments pushed the boundaries of technology. What did computational, cybernetic, and artificial intelligence researchers have to gain by engaging with architects and architectural problems? And what was this new space that emerged within these collaborations? At times, Steenson writes, the architects in this book characterized themselves as anti-architects and their work as anti-architecture. The projects Steenson examines mostly did not result in constructed buildings, but rather in design processes and tools, computer programs, interfaces, digital environments. Alexander, Wurman, Price, and Negroponte laid the foundation for many of our contemporary interactive practices, from information architecture to interaction design, from machine learning to smart cities.
‘The advent of machine learning-based AI systems demands that our industry does not just share toys, but builds a new sandbox in which to play with them.’ - Phil Bernstein The profession is changing. A new era is rapidly approaching when computers will not merely be instruments for data creation, manipulation and management, but, empowered by artificial intelligence, they will become agents of design themselves. Architects need a strategy for facing the opportunities and threats of these emergent capabilities or risk being left behind. Architecture’s best-known technologist, Phil Bernstein, provides that strategy. Divided into three key sections – Process, Relationships and Results – Machine Learning lays out an approach for anticipating, understanding and managing a world in which computers often augment, but may well also supplant, knowledge workers like architects. Armed with this insight, practices can take full advantage of the new technologies to future-proof their business. Features chapters on: Professionalism Tools and technologies Laws, policy and risk Delivery, means and methods Creating, consuming and curating data Value propositions and business models.
This book presents selected papers from The 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019). Focusing on novel architecture theories, tools, methods, and procedures for digital design and construction in architecture, it promotes dialogs between architecture, engineer, computer science, robotics, and other relevant disciplines to establish a new way of production in the building industry in the digital age. The contents make valuable contributions to academic researchers and engineers in the industry. At the same time, it offers readers new ideas for the application of digital technology.
Financial Times Best Books of the Year 2018 TechRepublic Top Books Every Techie Should Read Book Description How will AI evolve and what major innovations are on the horizon? What will its impact be on the job market, economy, and society? What is the path toward human-level machine intelligence? What should we be concerned about as artificial intelligence advances? Architects of Intelligence contains a series of in-depth, one-to-one interviews where New York Times bestselling author, Martin Ford, uncovers the truth behind these questions from some of the brightest minds in the Artificial Intelligence community. Martin has wide-ranging conversations with twenty-three of the world's foremost researchers and entrepreneurs working in AI and robotics: Demis Hassabis (DeepMind), Ray Kurzweil (Google), Geoffrey Hinton (Univ. of Toronto and Google), Rodney Brooks (Rethink Robotics), Yann LeCun (Facebook) , Fei-Fei Li (Stanford and Google), Yoshua Bengio (Univ. of Montreal), Andrew Ng (AI Fund), Daphne Koller (Stanford), Stuart Russell (UC Berkeley), Nick Bostrom (Univ. of Oxford), Barbara Grosz (Harvard), David Ferrucci (Elemental Cognition), James Manyika (McKinsey), Judea Pearl (UCLA), Josh Tenenbaum (MIT), Rana el Kaliouby (Affectiva), Daniela Rus (MIT), Jeff Dean (Google), Cynthia Breazeal (MIT), Oren Etzioni (Allen Institute for AI), Gary Marcus (NYU), and Bryan Johnson (Kernel). Martin Ford is a prominent futurist, and author of Financial Times Business Book of the Year, Rise of the Robots. He speaks at conferences and companies around the world on what AI and automation might mean for the future. Meet the minds behind the AI superpowers as they discuss the science, business and ethics of modern artificial intelligence. Read James Manyika’s thoughts on AI analytics, Geoffrey Hinton’s breakthroughs in AI programming and development, and Rana el Kaliouby’s insights into AI marketing. This AI book collects the opinions of the luminaries of the AI business, such as Stuart Russell (coauthor of the leading AI textbook), Rodney Brooks (a leader in AI robotics), Demis Hassabis (chess prodigy and mind behind AlphaGo), and Yoshua Bengio (leader in deep learning) to complete your AI education and give you an AI advantage in 2019 and the future.
This book explores the interdisciplinary project that brings the long tradition of humanistic inquiry in architecture together with cutting-edge research in artificial intelligence. The main goal of Neural Architecture is to understand how to interrogate artificial intelligence - a technological tool - in the field of architectural design, traditionally a practice that combines humanities and visual arts. Matias del Campo, the author of Neural Architecture is currently exploring specific applications of artificial intelligence in contemporary architecture, focusing on their relationship to material and symbolic culture. AI has experienced an explosive growth in recent years in a range of fields including architecture but its implications for the humanistic values that distinguish architecture from technology have yet to be measured. The book illustrates in a series of projects a set of crucial questions for the development of architecture in the future. An opportunity to survey the emerging field of Architecture and Artificial Intelligence, and to reflect on the implications of a world increasingly entangled in questions of the agency, culture and ethics of AI.
AI is already part of our lives even though we might not realise it. It is in our phones, filtering spam, identifying Facebook friends, and classifying our images on Instagram. It is in our homes in the form of Siri, Alexa and other AI assistants. It is in our cars and our planes. AI is literally everywhere. Artworks generated by AI have won international prizes, and have been sold at auction. But what does AI mean for the world of design? This issue of AD explores the nature of AI, and considers its potential for architecture. But this is no idle speculation. Architects have already started using AI for architectural design and fabrication. Yet – astonishingly – there has been almost no debate about AI within the discipline of architecture so far. Surely, nothing can be more important for the profession of architecture right now. The issue looks at all aspects of AI: its potential to assist architects in designing buildings so that it becomes a form of ‘augmented intelligence’; its capacity to design buildings on its own; and whether AI might open up an extraordinary new chapter in architectural design. Contributors: Refik Anadol; Daniel Bolojan; Alexa Carlson; Sofia Crespo and Feileacan McCormick; Gabriel Esquivel, Jean Jaminet and Shane Bugni; Behnaz Farahi; Theodoros Galanos and Angelos Chronis; Eduard Haiman; Wanyu He; Damjan Jovanovic and Lidija Kljakovic; Immanuel Koh; Maria Kuptsova; Sandra Manninger; Lev Manovich; Achim Menges and Thomas Wortmann; Wolf dPrix, Karolin Schmidbaur and Efilena Baseta; M Casey Rehm; and Hao Zheng and Masoud Akbarzadeh. Featured architects: Alisa Andrasek, Coop Himmelb(l)au, Lifeforms.io, Nonstandardstudio,SPAN, Kyle Steinfeld, Studio Kinch and Xkool Technology.
Ascend AI Processor Architecture and Programming: Principles and Applications of CANN offers in-depth AI applications using Huawei's Ascend chip, presenting and analyzing the unique performance and attributes of this processor. The title introduces the fundamental theory of AI, the software and hardware architecture of the Ascend AI processor, related tools and programming technology, and typical application cases. It demonstrates internal software and hardware design principles, system tools and programming techniques for the processor, laying out the elements of AI programming technology needed by researchers developing AI applications. Chapters cover the theoretical fundamentals of AI and deep learning, the state of the industry, including the current state of Neural Network Processors, deep learning frameworks, and a deep learning compilation framework, the hardware architecture of the Ascend AI processor, programming methods and practices for developing the processor, and finally, detailed case studies on data and algorithms for AI. - Presents the performance and attributes of the Huawei Ascend AI processor - Describes the software and hardware architecture of the Ascend processor - Lays out the elements of AI theory, processor architecture, and AI applications - Provides detailed case studies on data and algorithms for AI - Offers insights into processor architecture and programming to spark new AI applications