If you have ever looked at a fantastic adventure or science fiction movie, or an amazingly complex and rich computer game, or a TV commercial where cars or gas pumps or biscuits behaved liked people and wondered, “How do they do that?”, then you’ve experienced the magic of 3D worlds generated by a computer. 3D in computers began as a way to represent automotive designs and illustrate the construction of molecules. 3D graphics use evolved to visualizations of simulated data and artistic representations of imaginary worlds. In order to overcome the processing limitations of the computer, graphics had to exploit the characteristics of the eye and brain, and develop visual tricks to simulate realism. The goal is to create graphics images that will overcome the visual cues that cause disbelief and tell the viewer this is not real. Thousands of people over thousands of years have developed the building blocks and made the discoveries in mathematics and science to make such 3D magic possible, and The History of Visual Magic in Computers is dedicated to all of them and tells a little of their story. It traces the earliest understanding of 3D and then foundational mathematics to explain and construct 3D; from mechanical computers up to today’s tablets. Several of the amazing computer graphics algorithms and tricks came of periods where eruptions of new ideas and techniques seem to occur all at once. Applications emerged as the fundamentals of how to draw lines and create realistic images were better understood, leading to hardware 3D controllers that drive the display all the way to stereovision and virtual reality.

If you have ever looked at a fantastic adventure or science fiction movie, or an amazingly complex and rich computer game, or a TV commercial where cars or gas pumps or biscuits behaved liked people and wondered, “How do they do that?”, then you’ve experienced the magic of 3D worlds generated by a computer. 3D in computers began as a way to represent automotive designs and illustrate the construction of molecules. 3D graphics use evolved to visualizations of simulated data and artistic representations of imaginary worlds. In order to overcome the processing limitations of the computer, graphics had to exploit the characteristics of the eye and brain, and develop visual tricks to simulate realism. The goal is to create graphics images that will overcome the visual cues that cause disbelief and tell the viewer this is not real. Thousands of people over thousands of years have developed the building blocks and made the discoveries in mathematics and science to make such 3D magic possible, and The History of Visual Magic in Computers is dedicated to all of them and tells a little of their story. It traces the earliest understanding of 3D and then foundational mathematics to explain and construct 3D; from mechanical computers up to today’s tablets. Several of the amazing computer graphics algorithms and tricks came of periods where eruptions of new ideas and techniques seem to occur all at once. Applications emerged as the fundamentals of how to draw lines and create realistic images were better understood, leading to hardware 3D controllers that drive the display all the way to stereovision and virtual reality.

Data science addresses the need to extract knowledge and information from data volumes, often from real-time sources in a wide variety of disciplines such as astronomy, bioinformatics, engineering, science, medicine, social science, business, and the humanities. The range and volume of data sources has increased enormously over time, particularly those generating real-time data. This has posed additional challenges for data management and data analysis of the data and effective representation and display. A wide range of application areas are able to benefit from the latest visual tools and facilities. Rapid analysis is needed in areas where immediate decisions need to be made. Such areas include weather forecasting, the stock exchange, and security threats. In areas where the volume of data being produced far exceeds the current capacity to analyze all of it, attention is being focussed how best to address these challenges. Optimum ways of addressing large data sets across a variety of disciplines have led to the formation of national and institutional Data Science Institutes and Centers. Being driven by national priority, they are able to attract support for research and development within their organizations and institutions to bring together interdisciplinary expertise to address a wide variety of problems. Visual computing is a set of tools and methodologies that utilize 2D and 3D images to extract information from data. Such methods include data analysis, simulation, and interactive exploration. These are analyzed and discussed.

This is the first book in a three-part series that traces the development of the GPU. Initially developed for games the GPU can now be found in cars, supercomputers, watches, game consoles and more. GPU concepts go back to the 1970s when computer graphics was developed for computer-aided design of automobiles and airplanes. Early computer graphics systems were adopted by the film industry and simulators for airplanes and high energy physics—exploding nuclear bombs in computers instead of the atmosphere. A GPU has an integrated transform and lighting engine, but these were not available until the end of the 1990s. Heroic and historic companies expanded the development and capabilities of the graphics controller in pursuit of the ultimate device, a fully integrated self-contained GPU. Fifteen companies worked on building the first fully integrated GPU, some succeeded in the console, and Northbridge segments, and Nvidia was the first to offer a fully integrated GPU for the PC. Today the GPU can be found in every platform that involves a computer and a user interface.

Recent developments in computer technology are providing historians with new ways to see—and seek to hear, touch, or smell—traces of the past. Place-based augmented reality applications are an increasingly common feature at heritage sites and museums, allowing historians to create immersive, multifaceted learning experiences. Now that computer vision can be directed at the past, research involving thousands of images can recreate lost or destroyed objects or environments, and discern patterns in vast datasets that could not be perceived by the naked eye. Seeing the Past with Computers is a collection of twelve thought-pieces on the current and potential uses of augmented reality and computer vision in historical research, teaching, and presentation. The experts gathered here reflect upon their experiences working with new technologies, share their ideas for best practices, and assess the implications of—and imagine future possibilities for—new methods of historical study. Among the experimental topics they explore are the use of augmented reality that empowers students to challenge the presentation of historical material in their textbooks; the application of seeing computers to unlock unusual cultural knowledge, such as the secrets of vaudevillian stage magic; hacking facial recognition technology to reveal victims of racism in a century-old Australian archive; and rebuilding the soundscape of an Iron Age village with aural augmented reality. This volume is a valuable resource for scholars and students of history and the digital humanities more broadly. It will inspire them to apply innovative methods to open new paths for conducting and sharing their own research.

This scientific work focuses on computer-aided computational models in architecture. The author initially investigates established computational models and then expands these with newer approaches to modeling. In his research the author integrates approaches to analytical philosophy, probability theory, formal logic, quantum physics, abstract algebra, computer-aided design, computer graphics, glossematics, machine learning, architecture, and others. For researchers in the fields of information technology and architecture.

This is the second book in a three-part series that traces the development of the GPU, which is defined as a single chip with an integrated transform and lighting (T&L) capability. This feature previously was found in workstations as a stand-alone chip that only performed geometry functions. Enabled by Moore’s law, the first era of GPUs began in the late 1990s. Silicon Graphics (SGI) introduced T&L first in 1996 with the Nintendo 64 chipset with integrated T&L but didn’t follow through. ArtX developed a chipset with integrated T&L but didn’t bring it to market until November 1999. The need to integrate the transform and lighting functions in the graphics controller was well understood and strongly desired by dozens of companies. Nvidia was the first to produce a PC consumer level single chip with T&L in October 1999. All in all, fifteen companies came close, they had designs and experience, but one thing or another got in their way to prevent them succeeding. All the forces and technology were converging; the GPU was ready to emerge. Several of the companies involved did produce an integrated GPU, but not until early 2000. This is the account of those companies, the GPU and the environment needed to support it. The GPU has become ubiquitous and can be found in every platform that involves a computer and a user interface.