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General Will 2.0
by John Person Hiroki AzumaAccording to Azuma, the collective will and the general social contract has changed the world's political landscape over the last couple of years. Azuma looks back at Rousseau and Freud then forward to Twitter and Google to express how man deals with their part of the collective will through time. Azuma challenges society's perceptions of general will by looking at three philosophies through both time and technology. Azuma's unique analysis can be as compelling as fiction while making readers feel enlightened in the process.
Generalized Barycentric Coordinates in Computer Graphics and Computational Mechanics
by Kai Hormann N. SukumarIn Generalized Barycentric Coordinates in Computer Graphics and Computational Mechanics, eminent computer graphics and computational mechanics researchers provide a state-of-the-art overview of generalized barycentric coordinates. Commonly used in cutting-edge applications such as mesh parametrization, image warping, mesh deformation, and finite as well as boundary element methods, the theory of barycentric coordinates is also fundamental for use in animation and in simulating the deformation of solid continua. Generalized Barycentric Coordinates is divided into three sections, with five chapters each, covering the theoretical background, as well as their use in computer graphics and computational mechanics. A vivid 16-page insert helps illustrating the stunning applications of this fascinating research area. <P><P>Key Features: <li>Provides an overview of the many different types of barycentric coordinates and their properties. <li>Discusses diverse applications of barycentric coordinates in computer graphics and computational mechanics. <li>The first book-length treatment on this topic
Generalized Intuitionistic Multiplicative Fuzzy Calculus Theory and Applications (Uncertainty and Operations Research)
by Shan Yu Zeshui XuThis book mainly introduces the latest development of generalized intuitionistic multiplicative fuzzy calculus and its application. The book pursues three major objectives: (1) to introduce the calculus models with concrete mathematical expressions for generalized intuitionistic multiplicative fuzzy information; (2) to introduce new information fusion methods based on the definite integral models; and (3) to clarify the involved approaches bymilitary case. The book is especially valuable for readers to understand how the theoretical framework of generalized intuitionistic multiplicative fuzzy calculus is constructed, not only discrete or continuous but also correlative (generalized) intuitionistic (multiplicative) fuzzy information is aggregated based on the definite integral models and the theory with a military practice is integrated, which would deepen the understanding and give researchers more inspiration in practical decision analysis under uncertainties.
Generalized Linear Models With Examples in R (Springer Texts in Statistics)
by Peter K. Dunn Gordon K. SmythThis textbook presents an introduction to multiple linear regression, providing real-world data sets and practice problems. A practical working knowledge of applied statistical practice is developed through the use of these data sets and numerous case studies. The authors include a set of practice problems both at the end of each chapter and at the end of the book. Each example in the text is cross-referenced with the relevant data set, so that readers can load the data and follow the analysis in their own R sessions. The balance between theory and practice is evident in the list of problems, which vary in difficulty and purpose.This book is designed with teaching and learning in mind, featuring chapter introductions and summaries, exercises, short answers, and simple, clear examples. Focusing on the connections between generalized linear models (GLMs) and linear regression, the book also references advanced topics and tools that have not typically been included in introductions to GLMs to date, such as Tweedie family distributions with power variance functions, saddlepoint approximations, likelihood score tests, modified profile likelihood, and randomized quantile residuals. In addition, the authors introduce the new R code package, GLMsData, created specifically for this book. Generalized Linear Models with Examples in R balances theory with practice, making it ideal for both introductory and graduate-level students who have a basic knowledge of matrix algebra, calculus, and statistics.
Generalized Normalizing Flows via Markov Chains (Elements in Non-local Data Interactions: Foundations and Applications)
by Paul Lyonel Hagemann Johannes Hertrich Gabriele SteidlNormalizing flows, diffusion normalizing flows and variational autoencoders are powerful generative models. This Element provides a unified framework to handle these approaches via Markov chains. The authors consider stochastic normalizing flows as a pair of Markov chains fulfilling some properties, and show how many state-of-the-art models for data generation fit into this framework. Indeed numerical simulations show that including stochastic layers improves the expressivity of the network and allows for generating multimodal distributions from unimodal ones. The Markov chains point of view enables the coupling of both deterministic layers as invertible neural networks and stochastic layers as Metropolis-Hasting layers, Langevin layers, variational autoencoders and diffusion normalizing flows in a mathematically sound way. The authors' framework establishes a useful mathematical tool to combine the various approaches.
Generalized Statistical Thermodynamics: Thermodynamics of Probability Distributions and Stochastic Processes (Understanding Complex Systems)
by Themis MatsoukasThis book gives the definitive mathematical answer to what thermodynamics really is: a variational calculus applied to probability distributions. Extending Gibbs's notion of ensemble, the Author imagines the ensemble of all possible probability distributions and assigns probabilities to them by selection rules that are fairly general. The calculus of the most probable distribution in the ensemble produces the entire network of mathematical relationships we recognize as thermodynamics. The first part of the book develops the theory for discrete and continuous distributions while the second part applies this thermodynamic calculus to problems in population balance theory and shows how the emergence of a giant component in aggregation, and the shattering transition in fragmentation may be treated as formal phase transitions. While the book is intended as a research monograph, the material is self-contained and the style sufficiently tutorial to be accessible for self-paced study by an advanced graduate student in such fields as physics, chemistry, and engineering.
Generalizing from Limited Resources in the Open World: Second International Workshop, GLOW 2024, Held in Conjunction with IJCAI 2024, Jeju, South Korea, August 3, 2024, Proceedings (Communications in Computer and Information Science #2160)
by Jinyang Guo Yuqing Ma Yifu Ding Ruihao Gong Xingyu Zheng Changyi He Yantao Lu Xianglong LiuThis book presents the Proceedings from the Second International Workshop GLOW 2024 held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI 2024, in Jeju Island, South Korea, in August 2024. The 11 full papers and 4 short papers included in this book were carefully reviewed and selected from 22 submissions. They were organized in topical sections as follows: efficient methods for low-resource hardware; efficient fintuning with limited data; advancements in multimodal systems; recognition and reasoning in the open world.
Generating a New Reality: From Autoencoders and Adversarial Networks to Deepfakes
by Micheal LanhamThe emergence of artificial intelligence (AI) has brought us to the precipice of a new age where we struggle to understand what is real, from advanced CGI in movies to even faking the news. AI that was developed to understand our reality is now being used to create its own reality. In this book we look at the many AI techniques capable of generating new realities. We start with the basics of deep learning. Then we move on to autoencoders and generative adversarial networks (GANs). We explore variations of GAN to generate content. The book ends with an in-depth look at the most popular generator projects.By the end of this book you will understand the AI techniques used to generate different forms of content. You will be able to use these techniques for your own amusement or professional career to both impress and educate others around you and give you the ability to transform your own reality into something new.What You Will LearnKnow the fundamentals of content generation from autoencoders to generative adversarial networks (GANs)Explore variations of GANUnderstand the basics of other forms of content generationUse advanced projects such as Faceswap, deepfakes, DeOldify, and StyleGAN2Who This Book Is ForMachine learning developers and AI enthusiasts who want to understand AI content generation techniques
Generating Analog IC Layouts with LAYGEN II
by Nuno C. Lourenço Ricardo M. Martins Nuno C.G. HortaThis book presents an innovative methodology for the automatic generation of analog integrated circuits (ICs) layout, based on template descriptions and on evolutionary computational techniques. A design automation tool, LAYGEN II was implemented to validate the proposed approach giving special emphasis to reusability of expert design knowledge and to efficiency on retargeting operations.
Generation and Update of a Digital Twin in a Process Plant
by Josip Stjepandić Johannes Lützenberger Philipp KremerThis book covers the most important subjects of digital twin in a process plant, including foundations, methods, achievements, and applications in a brownfield environment. Besides offering a variety of applications and procedural variants from research and industrial practice, this book also provides a comprehensive insight into holistic plant planning. It also discusses the challenges that currently exist in different application areas. This book would be of interest to industry professionals and researchers in industrial and manufacturing engineering.
Generation Digital
by Kathryn C. MontgomeryChildren and teens today have integrated digital culture seamlessly into their lives. For most, using the Internet, playing videogames, downloading music onto an iPod, or multitasking with a cell phone is no more complicated than setting the toaster oven to "bake" or turning on the TV. In Generation Digital,media expert and activist Kathryn C. Montgomery examines the ways in which the new media landscape is changing the nature of childhood and adolescence and analyzes recent political debates that have shaped both policy and practice in digital culture. The media have pictured the so-called "digital generation" in contradictory ways: as bold trailblazers and innocent victims, as active creators of digital culture and passive targets of digital marketing. This, says Montgomery, reflects our ambivalent attitude toward both youth and technology. She charts a confluence of historical trends that made children and teens a particularly valuable target market during the early commercialization of the Internet and describes the consumer-group advocacy campaign that led to a law to protect children's privacy on the Internet. Montgomery recounts--as a participant and as a media scholar--the highly publicized battles over indecency and pornography on the Internet. She shows how digital marketing taps into teenagers' developmental needs and how three public service campaigns--about sexuality, smoking, and political involvement--borrowed their techniques from commercial digital marketers. Not all of today's techno-savvy youth are politically disaffected; Generation Digitalchronicles the ways that many have used the Internet as a political tool, mobilizing young voters in 2004 and waging battles with the music and media industries over control of cultural expression online. Montgomery's unique perspective as both advocate and analyst will help parents, politicians, and corporations take the necessary steps to create an open, diverse, equitable, and safe digital media culture for young people.
Generation Next
by Oli White**The bestselling debut novel from YouTube sensation Oli White. CONTAINS EXCLUSIVE BONUS CONTENT!**Things haven't been easy for Jack recently - life as a teenager has its ups and downs. But when he meets a new group of friends, who are every bit as geek as they are chic, his luck seems to be changing. Each of the group is talented and when they pool together to create Generation Next, an incredible new kind of social media platform, it's clear that they're on to something special.What if your Instagram account grew by hundreds of thousands of followers overnight, and big companies were fighting each other to offer you photoshoots? When GenNext suddenly goes viral, Jack and his friends are thrust into a crazy world of fame which is as terrifying as it is awesome. Because someone out there is determined to trip Jack up at every step. If he doesn't stop them, soon everyone he cares about - his friends, his family, and the girl he's falling for - will be in danger...
Generation Next
by Oli WhiteThe stunning debut novel from YouTube sensation Oli White. Includes an exclusive audiobook introduction read by Oli White.Things haven't been easy for Jack recently - life as a teenager has its ups and downs. But when he meets a new group of friends, who are every bit as geek as they are chic, his luck seems to be changing. Each of the group is talented and when they pool together to create Generation Next, an incredible new kind of social media platform, it's clear that they're on to something special. What if your Instagram account grew by hundreds of thousands of followers overnight, and big companies were fighting each other to offer you photoshoots? When GenNext suddenly goes viral, Jack and his friends are thrust into a crazy world of fame which is as terrifying as it is awesome. Because someone out there is determined to trip Jack up at every step. If he doesn't stop them, soon everyone he cares about - his friends, his family, and the girl he's falling for - will be in danger...(P)2016 Hodder & Stoughton
Generation Z: What It's Like to Grow up in the Age of Likes, LOLs and Longing
by The Washington PostAn in-depth profile of the digital native generation from the Pulitzer Prize-winning newspaper. For the generation after Millennials, technology has been the only way of life since birth. These children are the first group to have their formative moments chronicled on Facebook, to grow up surrounded by the ubiquity of smartphones, and most important, to navigate a social landscape ruled by the internet. With this lifestyle comes a host of issues that prior generations never dealt with, including cyberbullying, alienation from peers with greater access to technology, and an increasing vulnerability to online sexual predators. This series of articles from the Washington Post delves into the everyday lives of American kids and teenagers. With its exploration of the unique pressures and complications of living an online life (and most of life online), this collection is a must-read for anyone who cares about the future of Generation Z.
Generative Adversarial Learning: Architectures and Applications (Intelligent Systems Reference Library #217)
by Vasile Palade Roozbeh Razavi-Far Ariel Ruiz-Garcia Juergen SchmidhuberThis book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Adversarial learning fascinates the attention of machine learning communities across the world in recent years. Generative adversarial networks (GANs), as the main method of adversarial learning, achieve great success and popularity by exploiting a minimax learning concept, in which two networks compete with each other during the learning process. Their key capability is to generate new data and replicate available data distributions, which are needed in many practical applications, particularly in computer vision and signal processing. The book is intended for academics, practitioners, and research students in artificial intelligence looking to stay up to date with the latest advancements on GANs’ theoretical developments and their applications.
Generative Adversarial Networks and Deep Learning: Theory and Applications
by Roshani RautThis book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc. Features: Presents a comprehensive guide on how to use GAN for images and videos. Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GAN Highlights the inclusion of gaming effects using deep learning methods Examines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutions The book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum
Generative Adversarial Networks Cookbook
by Josh KalinThis book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.
Generative Adversarial Networks for Image Generation
by Xudong Mao Qing LiGenerative adversarial networks (GANs) were introduced by Ian Goodfellow and his co-authors including Yoshua Bengio in 2014, and were to referred by Yann Lecun (Facebook’s AI research director) as “the most interesting idea in the last 10 years in ML.” GANs’ potential is huge, because they can learn to mimic any distribution of data, which means they can be taught to create worlds similar to our own in any domain: images, music, speech, prose. They are robot artists in a sense, and their output is remarkable – poignant even. In 2018, Christie’s sold a portrait that had been generated by a GAN for $432,000. Although image generation has been challenging, GAN image generation has proved to be very successful and impressive. However, there are two remaining challenges for GAN image generation: the quality of the generated image and the training stability. This book first provides an overview of GANs, and then discusses the task of image generation and the details of GAN image generation. It also investigates a number of approaches to address the two remaining challenges for GAN image generation. Additionally, it explores three promising applications of GANs, including image-to-image translation, unsupervised domain adaptation and GANs for security. This book appeals to students and researchers who are interested in GANs, image generation and general machine learning and computer vision.
Generative Adversarial Networks in Practice
by Mehdi GhayoumiThis book is an all-inclusive resource that provides a solid foundation on Generative Adversarial Networks (GAN) methodologies, their application to real-world projects, and their underlying mathematical and theoretical concepts. Key Features: • Guides you through the complex world of GANs, demystifying their intricacies • Accompanies your learning journey with real-world examples and practical applications • Navigates the theory behind GANs, presenting it in an accessible and comprehensive way • Simplifies the implementation of GANs using popular deep learning platforms • Introduces various GAN architectures, giving readers a broad view of their applications • Nurture your knowledge of AI with our comprehensive yet accessible content • Practice your skills with numerous case studies and coding examples • Reviews advanced GANs, such as DCGAN, cGAN, and CycleGAN, with clear explanations and practical examples • Adapts to both beginners and experienced practitioners, with content organized to cater to varying levels of familiarity with GANs • Connects the dots between GAN theory and practice, providing a well-rounded understanding of the subject • Takes you through GAN applications across different data types, highlighting their versatility • Inspires the reader to explore beyond this book, fostering an environment conducive to independent learning and research • Closes the gap between complex GAN methodologies and their practical implementation, allowing readers to directly apply their knowledge • Empowers you with the skills and knowledge needed to confidently use GANs in your projects Prepare to deep dive into the captivating realm of GANs and experience the power of AI like never before with Generative Adversarial Networks (GANs) in Practice. This book brings together the theory and practical aspects of GANs in a cohesive and accessible manner, making it an essential resource for both beginners and experienced practitioners.
Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow and Keras
by Kailash AhirwarThis book is intended for data scientists, machine learning developers, deep learning practitioners and AI enthusiasts who want a project guide to test their knowledge and expertise in building real-world GANs models. These full-fledged projects will help you master machine learning, and neural network principles. Basic understanding of machine learning and deep learning concepts will be handy. Hands-on experience in Tensorflow or Keras will be a plus point
Generative AI: Navigating the Course to the Artificial General Intelligence Future
by Martin MusiolAn engaging and essential discussion of generative artificial intelligence In Generative AI: Navigating the Course to the Artificial General Intelligence Future, celebrated author Martin Musiol—founder and CEO of generativeAI.net and GenAI Lead for Europe at Infosys—delivers an incisive and one-of-a-kind discussion of the current capabilities, future potential, and inner workings of generative artificial intelligence. In the book, you'll explore the short but eventful history of generative artificial intelligence, what it's achieved so far, and how it's likely to evolve in the future. You'll also get a peek at how emerging technologies are converging to create exciting new possibilities in the GenAI space. Musiol analyzes complex and foundational topics in generative AI, breaking them down into straightforward and easy-to-understand pieces. You'll also find: Bold predictions about the future emergence of Artificial General Intelligence via the merging of current AI models Fascinating explorations of the ethical implications of AI, its potential downsides, and the possible rewards Insightful commentary on Autonomous AI Agents and how AI assistants will become integral to daily life in professional and private contexts Perfect for anyone interested in the intersection of ethics, technology, business, and society—and for entrepreneurs looking to take advantage of this tech revolution—Generative AI offers an intuitive, comprehensive discussion of this fascinating new technology.
Generative AI: How ChatGPT and Other AI Tools Will Revolutionize Business
by Tom TaulliThis book will show how generative technology works and the drivers. It will also look at the applications – showing what various startupsand large companies are doing in the space. There will also be a look at the challenges and risk factors.During the past decade, companies have spent billions on AI. But the focus has been on applying the technology to predictions – which is known as analytical AI. It can mean that you receive TikTok videos that you cannot resist. Or analytical AI can fend against spam or fraud or forecast when a package will be delivered. While such things are beneficial, there is much more to AI. The next megatrend will be leveraging the technology to be creative. For example, you could take a book and an AI model will turn it into a movie – at very little cost. This is all part of generative AI. It’s still in the nascent stages but it is progressing quickly. Generative AI can already create engaging blog posts, social media messages, beautiful artwork and compelling videos.The potential for this technology is enormous. It will be useful for many categories like sales, marketing, legal, product design, code generation, and even pharmaceutical creation.What You Will LearnThe importance of understanding generative AIThe fundamentals of the technology, like the foundation and diffusion modelsHow generative AI apps workHow generative AI will impact various categories like the law, marketing/sales, gaming, product development, and code generation.The risks, downsides and challenges.Who This Book is ForProfessionals that do not have a technical background. Rather, the audience will be mostly those in Corporate America (such as managers) as well as people in tech startups, who will need an understanding of generative AI to evaluate the solutions.
Generative AI For Dummies
by Pam BakerGenerate a personal assistant with generative AI Generative AI tools capable of creating text, images, and even ideas seemingly out of thin air have exploded in popularity and sophistication. This valuable technology can assist in authoring short and long-form content, producing audio and video, serving as a research assistant, and tons of other professional and personal tasks. Generative AI For Dummies is your roadmap to using the world of artificial intelligence to enhance your personal and professional lives. You'll learn how to identify the best platforms for your needs and write the prompts that coax out the content you want. Written by the best-selling author of ChatGPT For Dummies, this book is the ideal place to start when you're ready to fully dive into the world of generative AI. Discover the best generative AI tools and learn how to use them for writing, designing, and beyond Write strong AI prompts so you can generate valuable output and save time Create AI-generated audio, video, and imagery Incorporate AI into your everyday tasks for enhanced productivity This book offers an easy-to-follow overview of the capabilities of generative AI and how to incorporate them into any job. It's perfect for anyone who wants to add AI know-how into their work.
Generative AI for Effective Software Development
by Pekka Abrahamsson Anh Nguyen-Duc Foutse KhomhThis book provides a comprehensive, empirically grounded exploration of how Generative AI is reshaping the landscape of software development. It emphasizes the empirical evaluation of Generative AI tools in real-world scenarios, offering insights into their practical efficacy, limitations, and impact. By presenting case studies, surveys, and interviews from various software development contexts, the book offers a global perspective on the integration of Generative AI, highlighting how these advanced tools are adapted to and influence diverse cultural, organizational, and technological environments. This book is structured to provide a comprehensive understanding of Generative AI and its transformative impact on the field of software engineering. The book is divided into five parts, each focusing on different aspects of Generative AI in software development. As an introduction, Part 1 presents the fundamentals of Generative AI adoption. Part 2 is a collection of empirical studies and delves into the practical aspects of integrating Generative AI tools in software engineering, with a focus on patterns, methodologies, and comparative analyses. Next, Part 3 presents case studies that showcase the application and impact of Generative AI in various software development contexts. Part 4 then examines how Generative AI is reshaping software engineering processes, from collaboration and workflow to management and agile development. Finally, Part 5 looks towards the future, exploring emerging trends, future directions, and the role of education in the context of Generative AI. The book offers diverse perspectives as it compiles research and experiences from various countries and software development environments. It also offers non-technical discussions about Generative AI in management, teamwork, business and education. This way, it is intended for both researchers in software engineering and for professionals in industry who want to learn about the impactof Generative AI on software development.
Generative AI in Higher Education: The ChatGPT Effect
by Cecilia Ka Chan Tom CollotonChan and Colloton’s book is one of the first to provide a comprehensive examination of the use and impact of ChatGPT and Generative AI (GenAI) in higher education.Since November 2022, every conversation in higher education has involved ChatGPT and its impact on all aspects of teaching and learning. The book explores the necessity of AI literacy tailored to professional contexts, assess the strengths and weaknesses of incorporating ChatGPT in curriculum design, and delve into the transformation of assessment methods in the GenAI era. The authors introduce the Six Assessment Redesign Pivotal Strategies (SARPS) and an AI Assessment Integration Framework, encouraging a learner-centric assessment model. The necessity for well-crafted AI educational policies is explored, as well as a blueprint for policy formulation in academic institutions. Technical enthusiasts are catered to with a deep dive into the mechanics behind GenAI, from the history of neural networks to the latest advances and applications of GenAI technologies.With an eye on the future of AI in education, this book will appeal to educators, students and scholars interested in the wider societal implications and the transformative role of GenAI in pedagogy and research.