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R 1,780.00
Generative Adversarial Networks in Practice
Generative Adversarial Networks (GANs) in Practice is an all-inclusive resource that provides a solid foundation on 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, CycleGAN, and more, 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 the 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.
R 4,313.79
Nordic e-Infrastructure Tomorrow
This open access book constitutes the proceedings of the 6th Nordic e-Infrastructure Collaboration Conference, NeIC 2024, which took place in Tallinn, Estonia, in May 2024. The 14 papers included in this book were carefully reviewed and selected from 39 submissions. They deal with e-infrastructure focusing on topics like FAIR data stewardship,high-performance computing (HPC), sensitive data management, federated resource management, quantum computing, and AI-driven e-infrastructure solutions.
R 1,968.96
Generative AI for Multimedia Content Processing, Security and Privacy
Exploring the field of generative artificial intelligence (GenAI) and its use in the processing and security of multimedia content, this co-authored book addresses the critical needs and emerging challenges in the rapidly evolving intersection of artificial intelligence, multimedia content, and cybersecurity. The capabilities of sophisticated GenAI models in generating, improving, and manipulating multimedia information, including images, videos, and audio are thoroughly explored. Coverage also extends to technical innovations including advanced neural network topologies, novel training methods, and methods for boosting GenAI-generated content quality and authenticity. The book's focus on security and privacy concerns and the weaknesses brought on by GenAI includes data privacy challenges, the development of unlicensed material, and the exploitation of AI for nefarious intentions. Furthermore, the ethical implications and legal obstacles involved in guaranteeing the secure and accountable implementation of generative AI in multimedia applications are examined and potential future directions identified. Generative AI for Multimedia Content Processing, Security and Privacy: Fundamentals, advances and applications will be a useful reference for multimedia researchers and engineers working with GenAI, particularly those interested in security and privacy challenges. Cybersecurity researchers and engineers working on digital content security and synthetic media prevention, AI researchers and engineering and technology practitioners developing generative AI technologies, will all find relevant information in this volume. The book will also be of interest to regulatory and compliance experts, policy makers and regulators working on AI deployment and data protection; and digital rights and intellectual property specialists.
R 4,132.00
Beginner’s Guide to Generative AI
This book is the essential guide for anyone curious about AI's creative power. In the rapidly evolving landscape of artificial intelligence, generative AI stands out as one of the most transformative technologies of our time. Designed for beginners and requiring no prior knowledge of AI, this book breaks down the fundamentals of generative AI, from text and image generation to the workings of models like ChatGPT and Google Bard. The authors provide step-by-step coverage of the essential concepts and techniques that power generative AI. From the basics of how machines learn to generate text and images, to the intricate workings of models like Transformers, ChatGPT, and Google Bard, readers will gain a solid foundation in AI's most cutting-edge tools. Rather than focusing on a single method, the authors introduce a spectrum of generative modeling techniques, including diffusion models, variational autoencoders, and transformers. This comprehensive exposure ensures readers will be well-prepared to understand and adapt to the rapidly evolving AI landscape. In addition, real-world applications of generative AI across various industries are explored including healthcare innovations, business analytics, and legal technology, and the authors provide practical insights and examples that show how generative AI is revolutionizing these fields.
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Cambridge Handbook of Generative AI and the Law
This handbook offers an important exploration of generative AI and its legal and regulatory implications from interdisciplinary perspectives. The volume is divided into four parts. Part I provides the necessary context and background to understand the topic, including its technical underpinnings and societal impacts. Part II probes the emerging regulatory and policy frameworks related to generative AI and AI more broadly across different jurisdictions. Part III analyses generative AI's impact on specific areas of law, from non-discrimination and data protection to intellectual property, corporate governance, criminal law and more. Part IV examines the various practical applications of generative AI in the legal sector and public administration. Overall, this volume provides a comprehensive resource for those seeking to understand and navigate the substantial and growing implications of generative AI for the law.
R 8,246.80
Edge Computational Intelligence for AI-Enabled IoT Systems
Edge computational intelligence is an interface between Edge Computing and Artificial Intelligence (AI) technologies. This interfacing represents a paradigm shift in the world of work by enabling a broad application areas and customer-friendly solutions. Edge computational intelligence technologies are just in their infancy. Edge Computational Intelligence for AI-Enabled IoT Systems looks at the trends and advances in edge computing and edge AI, the services rendered by them, related security and privacy issues, training algorithms, architectures, and sustainable AI-enabled IoT systems.Together these technologies benefit from ultra-low latency, faster response times, lower bandwidth costs and resilience from network failure, and the book explains the advantages of systems and applications using intelligent IoT devices that are at the edge of a network and close to users. It explains how to make most of edge and cloud computing as complementary technologies or used in isolation for extensive and widespread applications. The advancement in IoT devices, networking facilities, parallel computation and 5G, and robust infrastructure for generalized machine learning have made it possible to employ edge computational intelligence in diverse areas and in diverse ways.The book begins with chapters that cover Edge AI services on offer as compared to conventional systems. These are followed by chapters that discuss security and privacy issues encountered during the implementation and execution of edge AI and computing services The book concludes with chapters looking at applications spread across different areas of edge AI and edge computing and also at the role of computational intelligence in AI-driven IoT systems.
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Learn Generative AI with PyTorch
Learn how generative AI works by building your very own models that can write coherent text, create realistic images, and even make lifelike music. Learn Generative AI with PyTorch teaches the underlying mechanics of generative AI by building working AI models from scratch. Throughout, you'll use the intuitive PyTorch framework that's instantly familiar to anyone who's worked with Python data tools. Along the way, you'll master the fundamentals of General Adversarial Networks (GANs), Transformers, Large Language Models (LLMs), variational autoencoders, diffusion models, LangChain, and more! In Learn Generative AI with PyTorch you'll build these amazing models: A simple English-to-French translatorA text-generating model as powerful as GPT-2A diffusion model that produces realistic flower imagesMusic generators using GANs and TransformersAn image style transfer modelA zero-shot know-it-all agent The generative AI projects you create use the same underlying techniques and technologies as full-scale models like GPT-4 and Stable Diffusion. You don't need to be a machine learning expert—you can get started with just some basic Python programming skills. About the technology: Transformers, Generative Adversarial Networks (GANs), diffusion models, LLMs, and other powerful deep learning patterns have radically changed the way we manipulate text, images, and sound. Generative AI may seem like magic at first, but with a little Python, the PyTorch framework, and some practice, you can build interesting and useful models that will train and run on your laptop. This book shows you how.
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Applications of AI and IoT in Geotechnical Engineering for Sustainable Infrastructure
Artificial intelligence (AI) and the Internet of Things (IoT) are transforming the way geotechnical engineers monitor, analyze, and manage soil‑structure systems. Applications of AI and IoT in Geotechnical Engineering for Sustainable Infrastructure explores how these emerging digital technologies can enhance decision‑making, improve infrastructure resilience, and support sustainable development in civil engineering projects. It examines the integration of AI and IoT in geotechnical engineering, including slope stability assessments, data‑driven techniques for soil classification and characterization, foundation and liquefaction analysis, optimizing earthwork practices and operations, tunnels, and earth‑retaining structures using real‑time sensor networks and data‑driven models. This book also discusses machine learning techniques for predicting soil behavior, real‑time monitoring of pile foundations, automated site investigation methods, and digital tools for risk assessment and infrastructure health monitoring/ assessment.This book is intended for researchers, graduate students, and practicing engineers in geotechnical and civil engineering. It will also benefit professionals working in smart infrastructure, disaster risk reduction, and infrastructure asset management who are interested in integrating digital technologies into sustainable engineering practice.
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Art and Ethics of Generative AI
Generative AI technologies are reshaping the way we create, communicate, and compute, presenting both unprecedented opportunities and profound challenges. As these systems increasingly influence decisions that shape our lives, it becomes clear that performance metrics alone cannot define their success. A deeper understanding of the intersection between technical innovation and human values is essential to navigate this transformative era.The Art and Ethics of Generative AI: Fairness, Transparency, and Human Values provides a balanced exploration of generative AI, combining technical insights with ethical considerations. It explains generative model architectures and learning paradigms in an accessible way, while addressing critical issues such as algorithmic bias, explainability challenges, and emerging regulatory approaches. Practical frameworks for responsible AI development are offered, alongside multidisciplinary perspectives that bridge technical and humanistic viewpoints. Abstract concepts are brought to life through practical illustrations, demonstrating how ethical considerations play out in real-world AI applications.Designed for a wide audience, the book serves AI practitioners seeking actionable guidance for building responsible systems, researchers exploring nuanced ethical dimensions, educators and students looking for comprehensive learning materials, and policymakers needing governance insights. It is an essential resource for anyone engaged in the rapidly evolving AI ecosystem.
R 5,165.00
Designing Instruction with Generative AI
Designing Instruction with Generative AI offers a novel set of tools and strategies for leveraging generative AI to create engaging and personalized learning experiences. While instructional designers are a tremendous asset to higher education, not all colleges or universities have the robust staff needed to support all instructors on staff or large student populations. Drawing on a wealth of research, professional experience, and strategic insights, this book equips new and seasoned teaching faculty and trainers with step-by-step directions on how freely accessible artificial intelligence software can assist with all aspects of the course creation and instruction process and cater to the needs of diverse learners. Each chapter offers forward-thinking and empirically validated ways to help faculty create and improve instructional materials, course design, and learning environments while supporting their digital literacies. Rather than introduce AI as a means of outsourcing subject-area expertise, critical thinking, or cognitive processes, the author instead emphasizes its potential to build on traditionally honed knowledge and foundational instructional design practices. From optimizing course alignment and accessibility practices to fostering active learning, motivation, and engagement, educators will find new solutions to common teaching and learning challenges with greater efficiency in time and capacity.The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC BY-NC-ND) 4.0 license.
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R 825.00
GenAI Security
This book is an essential guide for anyone looking to build secure and resilient generative AI applications. It provides actionable insights into identifying vulnerabilities and preventing attacks.Authored by security expert Paul Zenker, the book explores the critical aspects of securing GenAI systems across their lifecycle - design, development, and operation. Through numerous practical examples, detailed illustrations of threat scenarios, and application architectures, readers will gain a comprehensive understanding of potential risks. Step-by-step instructions cover techniques such as prompt injections, jailbreaks, and other attack vectors, equipping readers with the skills to anticipate and mitigate threats effectively.This resource is ideal for developers, security professionals, AI researchers, and organizations working with generative AI technologies. This book offers the tools and knowledge needed to create systems that can withstand sophisticated attacks in today’s high-stakes digital landscape.
R 2,564.00
Enhancing Security in Public Spaces Through Generative Adversarial Networks (GANs)
As the demand for data security intensifies, the vulnerabilities become glaring, exposing sensitive information to potential threats. In this tumultuous landscape, Generative Adversarial Networks (GANs) emerge as a groundbreaking solution, transcending their initial role as image generators to become indispensable guardians of data security. Within the pages of Enhancing Security in Public Spaces Through Generative Adversarial Networks (GANs), readers are guided through the intricate world of GANs, unraveling their unique design and dynamic adversarial training. The book presents GANs not merely as a technical marvel but as a strategic asset for organizations, offering a comprehensive solution to fortify cybersecurity, protect data privacy, and mitigate the risks associated with evolving cyber threats. It navigates the ethical considerations surrounding GANs, emphasizing the delicate balance between technological advancement and responsible use. Tailored for a diverse audience, the book speaks directly to organizations, researchers, government agencies, cybersecurity professionals, data privacy advocates, AI specialists, educational institutions, regulatory bodies, cybersecurity solution providers, and the general public. It provides actionable insights on integrating GANs into various sectors, offering a roadmap for leveraging their capabilities in healthcare, finance, smart cities, and beyond. Dive into the future of data security, armed with the knowledge and practical applications presented in this transformative book, as it unfolds the potential of GANs to safeguard our digital infrastructure in an era of unprecedented challenges.
R 12,550.49
Building Trust in the Generative Artificial Intelligence Era
In an era where generative artificial intelligence (AI) is reshaping industries and daily life, trust has become a cornerstone for its successful adoption and application. Building Trust in the Generative Artificial Intelligence Era: Technology Challenges and Innovations explores how trust can be built, maintained, and evaluated in a world increasingly reliant on AI technologies. Designed to be accessible to a broad audience, thi book blends theoretical insights with practical approaches, offering readers a comprehensive understanding of the topic.This book is divided into three parts. The first part examines the foundations of trust in generative AI, highlighting trends and ethical challenges such as "greenwashing" and remote work dynamics. The second part provides actionable frameworks and tools for assessing and enhancing trust, focusing on topics like cybersecurity, transparency, and explainability. The final section presents global case studies exploring university students' perceptions of ChatGPT, generative AI's applications in European agriculture, and its transformative impact on financial systems.By addressing both the opportunities and risks of generative AI, this book delivers groundbreaking insights for academics, professionals, and policymakers worldwide. It emphasizes practical solutions, ensuring readers gain the knowledge needed to navigate the evolving technological landscape and foster trust in transformative AI systems.
R 9,320.85
Generative Artificial Intelligence in Healthcare
Generative artificial intelligence (AI) is a transformative force in smart healthcare. It can produce contents virtually indistinguishable from human-created material, with the power to redefine healthcare and revolutionize how medical science interacts with technology. This book presents the potential applications and benefits of generative AI in healthcare and discusses its execution challenges and ethical aspects.Generative Artificial Intelligence in Healthcare: Current Practices and Future Development starts by reviewing the past and then discussing the present of generative AI-based systems and the potential challenges the future might bring. It then highlights the integration of generative AI with IoT and blockchain technologies along with offering case studies. The book explores how to integrate augmented and virtual reality into generative AI-based healthcare and covers the development of an effective machine algorithm for generative AI-based healthcare, as well as the design and implementation of generative adversarial networks (GANs) in healthcare systems.Discussions about data security and ergonomic design for healthcare products are also included in the book. This book will provide a platform for the past, present, and future of generative AI and will help researchers and healthcare practitioners generate more robust solutions.
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Understanding Infrastructure Edge Computing
UNDERSTANDING INFRASTRUCTURE EDGE COMPUTING A comprehensive review of the key emerging technologies that will directly impact areas of computer technology over the next five yearsInfrastructure edge computing is the model of data center and network infrastructure deployment which distributes a large number of physically small data centers around an area to deliver better performance and to enable new economical applications. It is vital for those operating at business or technical levels to be positioned to capitalize on the changes that will occur as a result of infrastructure edge computing.This book provides a thorough understanding of the growth of internet infrastructure from its inception to the emergence of infrastructure edge computing. Author Alex Marcham, an acknowledged leader in the field who coined the term ‘infrastructure edge computing,’ presents an accessible, accurate, and expansive view of the next generation of internet infrastructure. The book features illustrative examples of 5G mobile cellular networks, city-scale AI systems, self-driving cars, drones, industrial robots, and more—technologies that increase efficiency, save time and money, and improve safety. Covering state-of-the-art topics, this timely and authoritative book:Presents a clear and accurate survey of the key emerging technologies that will impact data centers, 5G networks, artificial intelligence and cyber-physical systems, and other areas of computer technologyExplores how and why Internet infrastructure has evolved to where it stands today and where it needs to be in the near futureCovers a wide range of topics including distributed application workload operation, infrastructure and application security, and related technologies such as multi-access edge computing (MEC) and fog computingProvides numerous use cases and examples of real-world applications which depend upon underlying edge infrastructureWritten for Information Technology practitioners, computer technology practitioners, and students, Understanding Infrastructure Edge Computing is essential reading for those looking to benefit from the coming changes in computer technology.
R 4,753.00
Hands-On Generative Adversarial Networks with Keras
Develop generative models for a variety of real-world use-cases and deploy them to productionKey FeaturesDiscover various GAN architectures using Python and Keras libraryUnderstand how GAN models function with the help of theoretical and practical examplesApply your learnings to become an active contributor to open source GAN applicationsBook DescriptionGenerative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning. This book will be your first step towards understanding GAN architectures and tackling the challenges involved in training them.This book opens with an introduction to deep learning and generative models, and their applications in artificial intelligence (AI). You will then learn how to build, evaluate, and improve your first GAN with the help of easy-to-follow examples. The next few chapters will guide you through training a GAN model to produce and improve high-resolution images. You will also learn how to implement conditional GANs that give you the ability to control characteristics of GAN outputs. You will build on your knowledge further by exploring a new training methodology for progressive growing of GANs. Moving on, you'll gain insights into state-of-the-art models in image synthesis, speech enhancement, and natural language generation using GANs. In addition to this, you'll be able to identify GAN samples with TequilaGAN.By the end of this book, you will be well-versed with the latest advancements in the GAN framework using various examples and datasets, and you will have the skills you need to implement GAN architectures for several tasks and domains, including computer vision, natural language processing (NLP), and audio processing.Foreword by Ting-Chun Wang, Senior Research Scientist, NVIDIAWhat you will learnLearn how GANs work and the advantages and challenges of working with themControl the output of GANs with the help of conditional GANs, using embedding and space manipulationApply GANs to computer vision, NLP, and audio processingUnderstand how to implement progressive growing of GANsUse GANs for image synthesis and speech enhancementExplore the future of GANs in visual and sonic artsImplement pix2pixHD to turn semantic label maps into photorealistic imagesWho this book is forThis book is for machine learning practitioners, deep learning researchers, and AI enthusiasts who are looking for a perfect mix of theory and hands-on content in order to implement GANs using Keras. Working knowledge of Python is expected.
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Generative AI for Effective Software Development
This 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 impact of Generative AI on software development.
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DeepSeek in Action
From fundamental concepts to advanced implementations, this book thoroughly explores the DeepSeek-V3 model, focusing on its Transformer-based architecture, technological innovations, and applications.The book begins with a thorough examination of theoretical foundations, including self-attention, positional encoding, the Mixture of Experts mechanism, and distributed training strategies. It then explores DeepSeek-V3’s technical advancements, including sparse attention mechanisms, FP8 mixed-precision training, and hierarchical load balancing, which optimize memory and energy efficiency. Through case studies and API integration techniques, the model's high-performance capabilities in text generation, mathematical reasoning, and code completion are examined. The book highlights DeepSeek’s open platform and covers secure API authentication, concurrency strategies, and real-time data processing for scalable AI applications. Additionally, the book addresses industry applications, such as chat client development, utilizing DeepSeek’s context caching and callback functions for automation and predictive maintenance.This book is aimed primarily at AI researchers and developers working on large-scale AI models. It is an invaluable resource for professionals seeking to understand the theoretical underpinnings and practical implementation of advanced AI systems, particularly those interested in efficient, scalable applications.
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Generative AI
This 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.
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Generative AI 2.0 and Data Analytics
Data analytics and generative AI (Gen AI) are transformative technologies that play a critical role in modern decision-making and innovation. Data analytics enables organizations to extract actionable insights from vast amounts of structured and unstructured data, driving efficiency, improving customer experiences, and identifying trends. Generative AI, on the other hand, enhances creativity and problem-solving by producing new content, such as text, images, and designs, based on learned patterns. Together, they empower people and organizations to make data-driven decisions, automate complex processes, and unlock new opportunities for growth and innovation.Generative AI 2.0 and Data Analytics explores the intersection between Gen AI and data analytics and addresses its profound efects on industries and organizations across the globe. Highlights of the book include:Deep learning architectures for generative models in business data managementOptimizing human-AI collaboration for strategic decision-making in business practisesBenchmarking practices and evaluation metrics for Generative AI in business data analyticsNot only covering the fundamental concepts, and techniques of generative AI and their practical application, the book also investigates how these techniques foster innovation and improve quality of data in various business domains. It examines a broad range of topics from artificial data generation, security analytics, anomaly detection, reinforcement management, ethical consideration, challenges and future scenarios. The book also features expert opinions and case studies to provide practical direction and valuable insight.
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