Generative design, once known only to insiders as a revolutionary method of creating artwork, models, and animations with programmed algorithms, has in recent years become a popular tool for designers. By using simple languages such as JavaScript in p5.js, artists and makers can create everything from interactive typography and textiles to 3D-printed furniture to complex and elegant infographics. This updated volume gives a jump-start on coding strategies, with step-by-step tutorials for creating visual experiments that explore the possibilities of color, form, typography, and images. Generative Design includes a gallery of all-new artwork from a range of international designers—fine art projects as well as commercial ones for Nike, Monotype, Dolby Laboratories, the musician Bjork, and others.
Generative design is a revolutionary new method of creating artwork, models, and animations from sets of rules, or algorithms. By using accessible programming languages such as Processing, artists and designers are producing extravagant, crystalline structures that can form the basis of anything from patterned textiles and typography to lighting, scientific diagrams, sculptures, films, and even fantastical buildings. Opening with a gallery of thirty-five illustrated case studies, Generative Design takes users through specific, practical instructions on how to create their own visual experiments by combining simple-to-use programming codes with basic design principles. A detailed handbook of advanced strategies provides visual artists with all the tools to achieve proficiency. Both a how-to manual and a showcase for recent work in this exciting new field, Generative Design is the definitive study and reference book that designers have been waiting for.
Generating form is one of the most fundamental aspects of architectural education and practice. While new computational tools are enabling ever more unpredictable forms, critics argue that this leads to a disconnection between architectural output and its context. This attractive, pocket-sized book uses 11 different architectural projects to explore how generative design processes can integrate digital as well as physical design tools and techniques to produce innovative forms that cohere with structural and material principles, performance and context. Illustrated with drawings, computer images and models, this stimulating, accessible handbook of ideas provides a guide for students as well as an inspiration for practising architects.
A bold and unprecedented look at a cutting-edge movement in architecture Toward a Living Architecture? is the first book-length critique of the emerging field of generative architecture and its nexus with computation, biology, and complexity. Starting from the assertion that we should take generative architects’ rhetoric of biology and sustainability seriously, Christina Cogdell examines their claims from the standpoints of the sciences they draw on—complex systems theory, evolutionary theory, genetics and epigenetics, and synthetic biology. She reveals significant disconnects while also pointing to approaches and projects with significant potential for further development. Arguing that architectural design today often only masquerades as sustainable, Cogdell demonstrates how the language of some cutting-edge practitioners and educators can mislead students and clients into thinking they are getting something biological when they are not. In a narrative that moves from the computational toward the biological and from current practice to visionary futures, Cogdell uses life-cycle analysis as a baseline for parsing the material, energetic, and pollution differences between different digital and biological design and construction approaches. Contrary to green-tech sustainability advocates, she questions whether quartzite-based silicon technologies and their reliance on rare earth metals as currently designed are sustainable for much longer, challenging common projections of a computationally designed and manufactured future. Moreover, in critiquing contemporary architecture and science from a historical vantage point, she reveals the similarities between eugenic design of the 1930s and the aims of some generative architects and engineering synthetic biologists today. Each chapter addresses a current architectural school or program while also exploring a distinct aspect of the corresponding scientific language, theory, or practice. No other book critiques generative architecture by evaluating its scientific rhetoric and disjunction from actual scientific theory and practice. Based on the author’s years of field research in architecture studios and biological labs, this rare, field-building book does no less than definitively, unsparingly explain the role of the natural sciences within contemporary architecture.
Studio environments can be defined as multi-dimensional integrated production spaces where basic design trainings take place and where design issues including theoretical notions such as sociological, political, phenomenological, and other dimensions are discussed. Present approaches within the literature and social media on this topic gives cause for students to evaluate their future professions over finished and pictorial products rather than ontological and processual means. While there are many resources available on the present approaches of aesthetics and visuality of interior spaces, there is not much research available on new design methodologies, related design processes, and new applied methods in interior arcitecture. Based on different contexts, these methods of design practice have the potential to enrich design processes and create multiple discussion platforms within project studios as well as other design media. These different representations and narration methods for research in the context of interior architecture can be effectively used in design processes. The Handbook of Research on Methodologies for Design and Production Practices in Interior Architecture proposes new design methodologies and related design processes and introduces new applied method approaches while presenting alternative methods that have been used within design studios in the field of interior architecture. The chapters deal with four major sections: the design process and interdiciplinary approaches; then scenario development and content; followed by material, texture, and atmosphere; and concluding with new approaches to design. While highlighting topics such as spatial perception, design strategies, architectural atmosphere, and design-thinking, this book is of interest to architects, interior designers, practitioners, stakeholders, researchers, academicians, and students looking for advanced research on the new design metholodologies and processes for interior architecture.
Summary Generative Art presents both the technique and the beauty of algorithmic art. The book includes high-quality examples of generative art, along with the specific programmatic steps author and artist Matt Pearson followed to create each unique piece using the Processing programming language. About the Technology Artists have always explored new media, and computer-based artists are no exception. Generative art, a technique where the artist creates print or onscreen images by using computer algorithms, finds the artistic intersection of programming, computer graphics, and individual expression. The book includes a tutorial on Processing, an open source programming language and environment for people who want to create images, animations, and interactions. About the Book Generative Art presents both the techniques and the beauty of algorithmic art. In it, you'll find dozens of high-quality examples of generative art, along with the specific steps the author followed to create each unique piece using the Processing programming language. The book includes concise tutorials for each of the technical components required to create the book's images, and it offers countless suggestions for how you can combine and reuse the various techniques to create your own works. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside The principles of algorithmic art A Processing language tutorial Using organic, pseudo-random, emergent, and fractal processes ================================================= Table of Contents Part 1 Creative Coding Generative Art: In Theory and Practice Processing: A Programming Language for ArtistsPart 2 Randomness and Noise The Wrong Way to Draw A Line The Wrong Way to Draw a Circle Adding Dimensions Part 3 Complexity Emergence Autonomy Fractals
Design occurs in a rich social context where the effectiveness and efficiency of social interaction and collective performance are key to successful outcomes. Increasingly, design is being explored and developed as a collective, collaborative, participatory, and even community process. The heightened recognition of designing as a social process has stimulated interest in collaborative design. This book contains the proceedings of the international conference "CoDesigning 2000" held in Coventry, England, September 2000. During this meeting exponents from a wide range of design domains came together to present and discuss perspectives on and new knowledge and understanding of collaborative design, and the evidence for enhanced design performance through collaboration. Within this volume different motivations for, conceptions of, and findings about collaborative design are addressed in 50 contributions by different research groups. Structured into 6 sections according to the main fields of interest, it provides a survey of the state of scientifically based knowledge and trends emerging from collaborative design research and their implications for a wide range of domains.
Are you working on a codebase where cost overruns, death marches, and heroic fights with legacy code monsters are the norm? Battle these adversaries with novel ways to identify and prioritize technical debt, based on behavioral data from how developers work with code. And that's just for starters. Because good code involves social design, as well as technical design, you can find surprising dependencies between people and code to resolve coordination bottlenecks among teams. Best of all, the techniques build on behavioral data that you already have: your version-control system. Join the fight for better code! Use statistics and data science to uncover both problematic code and the behavioral patterns of the developers who build your software. This combination gives you insights you can't get from the code alone. Use these insights to prioritize refactoring needs, measure their effect, find implicit dependencies between different modules, and automatically create knowledge maps of your system based on actual code contributions. In a radical, much-needed change from common practice, guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Discover a comprehensive set of practical analysis techniques based on version-control data, where each point is illustrated with a case study from a real-world codebase. Because the techniques are language neutral, you can apply them to your own code no matter what programming language you use. Guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Apply research findings from social psychology to software development, ensuring you get the tools you need to coach your organization towards better code. If you're an experienced programmer, software architect, or technical manager, you'll get a new perspective that will change how you work with code. What You Need: You don't have to install anything to follow along in the book. TThe case studies in the book use well-known open source projects hosted on GitHub. You'll use CodeScene, a free software analysis tool for open source projects, for the case studies. We also discuss alternative tooling options where they exist.
Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN
