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Change is one of the most significant parameters in our society. Designers are amongst the primary change agents for any society. As a consequence design is an important research topic in engineering and architecture and related disciplines, since design is not only a means of change but is also one of the keystones to economic competitiveness and the fundamental precursor to manufacturing. The development of computational models founded on the artificial intelligence paradigm has provided an impetus for much of current design research -both computational and cognitive. These forms of design research have only been carried out in the last decade or so and in the temporal sense they are still immature. Notwithstanding this immaturity, noticeable advances have been made both in extending our understanding of design and in developing tools based on that understanding. Whilst many researchers in the field of artificial intelligence in design utilise ideas about how humans design as one source of concepts there is normally no attempt to model human designers. Rather the results of the research presented in this volume demonstrate approaches to increasing our understanding of design as a process.
Artificial Intelligence (AI) Design and Solutions for Risk and Security targets readers to understand, learn, define problems, and architect AI projects. Starting from current business architectures and business processes to futuristic architectures. Introduction to data analytics and life cycle includes data discovery, data preparation, data processing steps, model building, and operationalization are explained in detail. The authors examine the AI and ML algorithms in detail, which enables the readers to choose appropriate algorithms during designing solutions. Functional domains and industrial domains are also explained in detail. The takeaways are learning and applying designs and solutions to AI projects with risk and security implementation and knowledge about futuristic AI in five to ten years.
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.
This book introduces the reader to Artificial Intelligence and its importance to our future. Campbell uses behavioural psychology, explores technology, economics, real-life and historical examples to predict five future scenarios with AI. Illustrating through speculative fiction, she describes possible futures after AI exceeds human capabilities. We are at a tipping point in history and must plan to ensure a successful co-existence with artificial intelligence. This book explains how to design for a future with AI so that, rather than herald our downfall, it helps us achieve a new renaissance.
Von der Produktidee über den Prototyp und die Modellsimulation bis zur Analyse: Dieser Band hilft Entwicklern und Designern beim Verständnis aller Abläufe im Zuge des Designs neuer Produkte, Prozesse und Systeme. Eine Fülle von Beispielen industrieller Anwendungen, realer Probleme und zugehöriger Lösungen hilft beim Vertiefen und Umsetzen des Stoffes. (05/00)
A collection of fourteen essays which provide an overview of the argument for intelligent design, with diagrams, explanations, and relevant quotations.
Big Data, Big Design provides designers with the tools they need to harness the potential of machine learning and put it to use for good through thoughtful, human-centered, intentional design. Enter the world of Machine Learning (ML) and Artificial Intelligence (AI) through a design lens in this thoughtful handbook of practical skills, technical knowledge, interviews, essays, and theory, written specifically for designers. Gain an understanding of the design opportunities and design biases that arise when using predictive algorithms. Learn how to place design principles and cultural context at the heart of AI and ML through real-life case studies and examples. This portable, accessible guide will give beginners and more advanced AI and ML users the confidence to make reasoned, thoughtful decisions when implementing ML design solutions.
Mind design is the endeavor to understand mind (thinking, intellect) in terms of its design (how it is built, how it works). Unlike traditional empirical psychology, it is more oriented toward the "how" than the "what." An experiment in mind design is more likely to be an attempt to build something and make it work—as in artificial intelligence—than to observe or analyze what already exists. Mind design is psychology by reverse engineering. When Mind Design was first published in 1981, it became a classic in the then-nascent fields of cognitive science and AI. This second edition retains four landmark essays from the first, adding to them one earlier milestone (Turing's "Computing Machinery and Intelligence") and eleven more recent articles about connectionism, dynamical systems, and symbolic versus nonsymbolic models. The contributors are divided about evenly between philosophers and scientists. Yet all are "philosophical" in that they address fundamental issues and concepts; and all are "scientific" in that they are technically sophisticated and concerned with concrete empirical research. Contributors Rodney A. Brooks, Paul M. Churchland, Andy Clark, Daniel C. Dennett, Hubert L. Dreyfus, Jerry A. Fodor, Joseph Garon, John Haugeland, Marvin Minsky, Allen Newell, Zenon W. Pylyshyn, William Ramsey, Jay F. Rosenberg, David E. Rumelhart, John R. Searle, Herbert A. Simon, Paul Smolensky, Stephen Stich, A.M. Turing, Timothy van Gelder
The book contains the papers developed from the presentations at the Distributed Intelligence in Design Symposium, held in Salford in May 2009. In this context, Distributed Intelligence refers to the interdisciplinary knowledge of a range of different individuals in different organisations, with different backgrounds and experience, and the symposium discussed the media, technologies and behaviours required to support their successful collaboration. The book focusses on: how parametric and generative design media can be coupled with and managed alongside Building Information Modelling tools and systems how the cross-disciplinary knowledge is distributed and coordinated across different software, participants and organizations the characteristics of the evolving creative and collaborative practices how built environment education should be adapted to this digitally-networked practice and highly distributed intelligence in design The chapters address a range of innovative developments, methodologies, applications, research work and theoretical arguments, to present current experience and expectations as collaborative practice becomes critical in the design of future built environments.
Includes the leading names, movements, materials and processes such as furniture, fashion, cars, graphics, products, signs and symbols that have influenced the world of design.