Search results for "Generative AI Modeling"
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Role of Generative AI in the Communication Classroom
In an era marked by the rapid integration of Artificial Intelligence (AI) into our lives, the discourse surrounding its implications has intensified. The Role of Generative AI in the Communication Classroom is a pioneering book that delves into the multifaceted dimensions of AI, specifically focusing on OpenAI's revolutionary Chat Generative Pre-Trained Transformer (Chat GPT) and its profound influence on the landscape of communication education. This book navigates the intersection of technology, education, and ethics, shedding light on the imperative need for a collaborative approach to shape AI's evolution. AI's potential to reshape industries and human roles is undeniable. Rooted in the intricate workings of AI and its hallmark, Chat GPT, this book meticulously dissects the dynamic relationship between humans and machines. The discourse extends beyond technology and into the realm of education, asserting that the power to mold AI's trajectory cannot rest solely in the hands of developers. Collaboration involving educators and policymakers is fundamental to ensure AI's ethical and inclusive deployment in education. With an eye on the future, this book advocates for curriculum adaptations that cater to the digital generation, whose lives are intertwined with AI. Addressing the symbiotic interaction of AI and communication, it underscores the significance of communication studies engaging with AI to leverage its potential to foster societal benefits. While revealing AI's transformative potential in the communication classroom, the book conscientiously explores ethical concerns and biases, fostering a balanced approach to its integration. This book is instrumental to the ongoing discourse on AI's role in education. The call for ethical considerations, inclusivity, and regulation serves as a guiding compass for educators, students, developers, and policymakers alike. The book ensures a holistic perspective on AI's integration by addressing privacy, citation, voice ownership, and overall digital ethics. Targeting academic communities and organizations focused on communication, media studies, and AI in education, The Role of Generative AI in the Communication Classroom is an essential read. It aligns seamlessly with the agendas of educational departments across universities, presenting an insightful synthesis of computer science, education, and communication studies. By engaging with relevant conferences and journals, this book invigorates discussions and steers education toward a balanced and responsible AI-driven future.
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Generative AI in the English Composition Classroom
Designed to cater to the needs of both novice and seasoned writing instructors, this book provides a range of practical and adaptable strategies for integrating generative artificial intelligence (AI) into English writing curricula.Generative AI in the English Composition Classroom proposes strategic methodologies to ensure that AI is utilized as a facilitator of learning and creativity, rather than as a shortcut to academic success. With a particular emphasis on sophisticated large language models such as Claude, ChatGPT, and Gemini, this book critically addresses potential challenges, including concerns related to academic integrity. It includes case studies and practical strategies to exemplify how AI can enhance the writing process while emphasizing the continuing importance of a solid foundation in writing structure, processes, and rhetorical strategies. These case studies and strategies are designed for immediate application, offering educators and students practical tools to effectively navigate AI-augmented writing environments. Finally, the book looks to the future, discussing the evolving skillsets required in the workforce and how educators can equip students for a future in which AI is an integral component.A forward-thinking and invaluable guide, this book will be of interest to educators involved in teaching English Composition and writing.
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Understanding the Ethical Concerns of Generative AI
This textbook is designed to help readers navigate a world increasingly shaped by generative AI technologies. It prepares readers to confront issues such as bias, sustainability, transparency, and privacy as these technologies become more ubiquitous in daily life. Emphasis is placed on developing a theoretical foundation for ethical behavior and understanding the new ethical concerns that emerge from the use of generative AI.
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Generative AI with SAP and Amazon Bedrock
Explore Generative AI and understand its key concepts, architecture, and tangible business use cases. This book will help you develop the skills needed to use SAP AI Core service features available in the SAP Business Technology Platform.You’ll examine large language model (LLM) concepts and gain the practical knowledge to unleash the best use of Gen AI. As you progress, you’ll learn how to get started with your own LLM models and work with Generative AI use cases. Additionally, you’ll see how to take advantage Amazon Bedrock stack using AWS SDK for ABAP.To fully leverage your knowledge, Generative AI with SAP and Amazon Bedrock offers practical step-by-step instructions for how to establish a cloud SAP BTP account model and create your first GenAIartifacts. This work is an important prerequisite for those who want to take full advantage of generative AI with SAP.What You Will LearnMaster the concepts and terminology of artificial intelligence and GenAIUnderstand opportunities and impacts for different industries with GenAIBecome familiar with SAP AI Core, Amazon Bedrock, AWS SDK for ABAP and develop your firsts GenAI projectsAccelerate your development skillsGain more productivity and time implementing GenAI use casesWho this Book Is ForAnyone who wants to learn about Generative AI for Enterprise and SAP practitioners who want to take advantage of AI within the SAP ecosystem to support their systems and workflows.
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Data Lakehouse Revolution
We are racing toward a new kind of AI--faster, smarter, and more connected than ever. At the heart of it is the Data Lakehouse, and Databricks is the engine powering the transformation. Whether you're a data scientist training models, an engineer scaling pipelines, or an architect modernizing your stack, this book gives you what you need to stay ahead. Inside, you'll understand how to unlock the full potential of Machine Learning and Generative AI (GenAI) using Databricks--no fluff, just real tools, real strategies, and real results. From MLFlow and AutoML to Unity Catalog, Retrieval Augment Generation (RAG), and Vector Search, you'll get a complete blueprint for building intelligent systems that actually work in production. With step-by-step labs, industry case studies, and expert tips from someone who's lived through the entire evolution of enterprise AI, this book is your guide to mastering what's next. If you're serious regarding building AI that matters, this is where your journey begins. What You'll Learn Build full-stack ML and GenAI solutions on Databricks Train and track models with MLFlow, AutoML, and tuning strategies Secure and govern data with Unity Catalog Apply explainable, ethical AI techniques Deploy and monitor ML models in real-world pipelines Use RAG and vector search to power GenAI applications Gain confidence with hands-on labs and real enterprise use cases Who This Book Is For Azure administrators, data architects, and data engineers
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Generative AI and Education
This volume addresses the gap in knowledge around generative AI and its applications in education. It draws on the recent history of technological innovation and digital pedagogies, locating generative AI in the contemporary discourse around education futures. It argues that a new hybrid model of education is emerging, requiring educational institutions to embed generative AI into course and programme design, delivery and assessment. It also proposes a shift from a focus on learning as output to learning as a process, and explores what that shift might look like. Grounded in educational theory, it offers actionable pedagogy-informed guidance on how to position AI as a collaborator in the construction of learning in a manner that is congruent with the values and aims of education. It offers advice based on evidence-based digital pedagogy, including frameworks for effective teaching and learning with generative AI, that enable educators and designers to put these ideas into practice.The book also explores the wider context informing this shift, connecting narratives from governments and industry leaders on the strategic importance of generative AI and lifelong learning, learning agility, and future skills that make the case for the integration of competency-based assessment into mainstream education. Finally, going beyond pedagogy and practice, it considers of some of the broader issues, including limitations and ethics, and the implications of integrating generative AI into institutional planning and design, and includes a sample roadmap for education leaders to start the process of integrating generative AI into their institutions.This work approaches the topic of generative AI from the vantage point of educators by addressing themes and concerns that will resonate with professionals in the sector.
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Information Access in the Era of Generative AI
Generative Artificial Intelligence (GenAI) has emerged as a groundbreaking technology that promises to revolutionize many industries as well as people’s personal and professional lives. This book discusses GenAI and its role in information access - often referred to as Generative Information Retrieval (GenIR) - or more broadly, information interaction.The role of GenAI in information access is complex and dynamic, with many dimensions. To address this, following a brief introduction to GenAI and GenIR, the remainder of the book provides eight chapters, each targeting a different dimension or sub-topic. These cover foundations of GenIR, interactions with GenIR systems, adapting them to users, tasks, and scenarios, improving them based on user feedback, GenIR evaluation, the sociotechnical implications of GenAI for information access, recommendations within GenIR, and the future of information access with GenIR.The book is targeted at graduate students and researchers interested in issues of information retrieval, access, and interactions, as well as applications of GenAI in various informational contexts. While some of the parts assume prior background in IR or AI, most others do not, making this book suitable for adoption in various classes as a primary source or as a supplementary material.
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Generative AI in the English Composition Classroom
Designed to cater to the needs of both novice and seasoned writing instructors, this book provides a range of practical and adaptable strategies for integrating generative AI into English writing curricula.Generative AI in the English Composition Classroom proposes strategic methodologies to ensure that AI is utilized as a facilitator of learning and creativity, rather than as a shortcut to academic success. With a particular emphasis on sophisticated large language models such as Claude, ChatGPT, and Gemini, this book critically addresses potential challenges, including concerns related to academic integrity. It includes case studies and practical strategies to exemplify how AI can enhance the writing process while emphasizing the continuing importance of a solid foundation in writing structure, processes, and rhetorical strategies. These case studies and strategies are designed for immediate application, offering educators and students practical tools to effectively navigate AI-augmented writing environments. Finally, the book looks to the future, discussing the evolving skillsets required in the workforce and how educators can equip students for a future in which AI is an integral component.A forward-thinking and invaluable guide, this book will be of interest to educators involved in teaching English composition and writing.
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Next-Generation Recommendation Systems
A detailed guide to building cutting-edge recommendation systems In Next-Generation Recommendation Systems: A Comprehensive Guide to Enabling Technologies and Tools and their Business Benefits, a team of experienced technologists and educators, each with a proven track record in the field, delivers an expert guide to building robust recommendation systems that can interface with complex databases. The authors’ deep understanding of the subject matter is evident as they explain how to use the latest AI technologies, including LLMs, graph neural networks, diffusion models, and generative adversarial networks, to create recommendation engines that users enjoy and that drive business revenue. The book does not just delve into theoretical concepts, but also connects them to advanced implementation techniques. It demonstrates the application of practical and adaptable techniques, such as graph embeddings and Bayesian networks, to solve real-world problems faced by platform users and businesses. Readers will find the knowledge and tools to tackle these challenges head-on. Comprehensive coverage of practical generative AI techniques, including large language models and diffusion models Detailed exploration of graph neural networks and knowledge graph embeddings to solve common recommendation engine problems Practical guidance on implementing generative adversarial networks and variational autoencoders to address mode collapse and information bottleneck challenges In-depth analysis of hybrid recommendation architectures that combine content-based, collaborative, and knowledge-based filtering Real-world deployment strategies using cloud-native computing environments are not just theoretical concepts in this book. They are actionable strategies that have been tested and proven effective. This emphasis on real-world applicability will reassure readers about the book’s relevance to their professional or academic pursuits. Perfect for data scientists, AI specialists, software engineers, architects, and graduate students, Next-Generation Recommendation Systems is an essential, up-to-date resource for everyone involved in the design, deployment, and optimization of recommendation systems that connect to large, complex datasets.
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AI and ML for Coders in Pytorch
Eager to learn AI and machine learning but unsure where to start? Laurence Moroney's hands-on, code-first guide demystifies complex AI concepts without relying on advanced mathematics. Designed for programmers, it focuses on practical applications using PyTorch, helping you build real-world models without feeling overwhelmed.From computer vision and natural language processing (NLP) to generative AI with Hugging Face Transformers, this book equips you with the skills most in demand for AI development today. You'll also learn how to deploy your models across the web and cloud confidently.Gain the confidence to apply AI without needing advanced math or theory expertiseDiscover how to build AI models for computer vision, NLP, and sequence modeling with PyTorchLearn generative AI techniques with Hugging Face Diffusers and Transformers
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Practical Guide to Using Generative AI in Photoshop
Your guide to the world of Generative AI in Photoshop! Everyone s talking about the new Generative AI capabilities of Adobe Photoshop, and for good reason: This is the biggest update to Photoshop in its history. With the power of AI photo editing, you can now remove, expand, generate, change, or combine almost anything you need to in order to create the images you want. While these features are incredibly powerful, it can be a struggle to get the best results from these powerful tools. What exactly can Generative Fill and Generative Expand do, and how do they do it? When should you use these tools, and when should you use another tool? If you want to incorporate these tools into your workflow, it s very important to get an early grasp of these tools now and get ahead of the crowd. In this book, bestselling author Colin Smith walks you through Generative AI in Photoshop. With decades of experience working in the real world and training for Adobe, Apple, Nvidia, and many others, he knows Photoshop on a level that few do. He also has a knack for making learning fun and easy, and he can take complex topics and make them seem simple. You will learn to: Generate a scene from scratch Extend an image Fix panoramas Remove crowds Remove any object Generate objects Replace objects Duplicate and move an image Combine variations of generated images Blend images into an extended scene Repair old or damaged photos Composite with your own photos Composite your photo into an AI scene Change backgrounds Add reflections Generate depth of field Create actions with Generative AI commands And much more! Make no mistake: Generative AI is here to stay, and it is revolutionizing how we work in Photoshop. With The Practical Guide to Using Generative AI in Photoshop by your side, you will be ready to confidently move forward with these new tools and apply them to your own imagery. Whether you want to simply clean up your photos or create fantastical works of art or anything in between your only limitation will be your imagination.
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Generative AI in Higher Education:Guiding Principles for Teaching and Learning
Divided into two volumes, this book develops guiding principles for higher education institutions to use GenAI effectively and ethically in teaching and learning, articulating a roadmap for implementation at institutional levels and addressing the conundrum of using GenAI in higher education. As higher education institutions take different attitudes and approaches to Generative AI (GenAI), with some viewing it as a threat to academic integrity and therefore implementing a policy of banning its use, while others have embraced it as an innovation to academic practice and have implemented guidance on how to use it ethically, this book makes clear that GenAI , such as ChatGPT, is not the problem itself, but rather the issue is how we engage with it.
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Deep Generative Models
This book constitutes the proceedings of the 5th Workshop on Deep Generative Models for Medical Image Computing and Computer Assisted Intervention, DGM4MICCAI 2025, held in conjunction with the 28th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, in Daejeon, South Korea, during September 2025.The 33 papers presented in this book were carefully reviewed and selected from 50 submissions. These papers deal with recent algorithmic developments, new results, and promising future directions in Deep Generative Models.
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Generative AI for Cybersecurity
This book lays a systematic foundation for professionals, researchers, and industry readers who are interested the applications and implications of generative AI for cybersecurity. It covers the latest advances in generative AI and its applications, risks, and opportunities in cybersecurity.The authors first introduce the fundamental background of generative AI, the latest cybersecurity issues, and related potential applications in cybersecurity systems. Following this, they comprehensively review the state-of-the-art research and development, covering various aspects of generative AI applications in this area and related challenges and issues, such as training data availability, computational complexity, generalization to different scenarios, AI governance, quantum-empowered AI and many more. These discussions provide a strong understanding of recent advances in the two fields of generative AI and cybersecurity and the convergence of these domains, which will help readers to shape the field as it matures. Hands-on experiments presented throughout will also give them the practical skills for success. By leveraging its capabilities, readers can overcome challenges, understand the risks, enhance performance, and unlock new opportunities for handling the challenges of cybersecurity with generative AI. Consequently, they will be able to apply their knowledge to utilize generative AI in cybersecurity applications to prevent economic and other losses due to cyber risks such as phishing, fake news, deepfake-based fraud, and other cyberattacks.The contents of this book are appropriate for a wide range of readers from general readers to industry experts and scientists. Because it bridges the gap between generative AI and cybersecurity, experts from both fields will benefit from the information presented within. Students with a background in either area will also benefit from the approach that leads from general to specific applications.
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Generative AI and Cyberbullying
Ever since the COVID-19 pandemic occurred in 2020, the world has transformed itself greatly ever since them. For example, not only is the near 99% remote workforce now a reality, but businesses today are taking Incident Response and Disaster Recovery much more seriously these days as well. But another area that has blossomed in the last couple of years has been that of Generative AI. It is actually a subfield of Artificial Intelligence, which has been around since the 1950s.But Gen AI (as it is also called) has been fueled by the technology of ChatGPT, which has been developed and created by OpenAI. Given the GPT4 Algorithms that is powered by, an end user can merely type in, or even speak into the platform a query, and an output that is specific to that query will be automatically generated. The answer (or “output”) can be given as a text, video, image, or even an audio file.The scalability and diversity of Gen AI has allowed it be used in a wide myriad of industries and applications. But although it has been primarily designed to serve the greater good, it can also be used for very nefarious purposes, such as Online Harassment and Cyberbullying. In this particular book, we actually take the good side of Gen AI, provide an overview as to how it can be used to help combat Cyberbullying. This book is broken down into the following topics:Ø What Cyberbullying Is All AboutØ How Technology (Gen AI) Can Be Used To Combat CyberbullyingØ An Overview Into Gen AIØ Advanced Topics Into Gen AIØ Conclusions
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Generative AI for Cloud Solutions
Explore Generative AI, the engine behind ChatGPT, and delve into topics like LLM-infused frameworks, autonomous agents, and responsible innovation, to gain valuable insights into the future of AI Key FeaturesGain foundational GenAI knowledge and understand how to scale GenAI/ChatGPT in the cloudUnderstand advanced techniques for customizing LLMs for organizations via fine-tuning, prompt engineering, and responsible AIPeek into the future to explore emerging trends like multimodal AI and autonomous agentsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionGenerative artificial intelligence technologies and services, including ChatGPT, are transforming our work, life, and communication landscapes. To thrive in this new era, harnessing the full potential of these technologies is crucial. Generative AI for Cloud Solutions is a comprehensive guide to understanding and using Generative AI within cloud platforms.This book covers the basics of cloud computing and Generative AI/ChatGPT, addressing scaling strategies and security concerns. With its help, you’ll be able to apply responsible AI practices and other methods such as fine-tuning, RAG, autonomous agents, LLMOps, and Assistants APIs. As you progress, you’ll learn how to design and implement secure and scalable ChatGPT solutions on the cloud, while also gaining insights into the foundations of building conversational AI, such as chatbots. This process will help you customize your AI applications to suit your specific requirements.By the end of this book, you’ll have gained a solid understanding of the capabilities of Generative AI and cloud computing, empowering you to develop efficient and ethical AI solutions for a variety of applications and services.What you will learnGet started with the essentials of generative AI, LLMs, and ChatGPT, and understand how they function togetherUnderstand how we started applying NLP to concepts like transformersGrasp the process of fine-tuning and developing apps based on RAGExplore effective prompt engineering strategiesAcquire insights into the app development frameworks and lifecycles of LLMs, including important aspects of LLMOps, autonomous agents, and Assistants APIsDiscover how to scale and secure GenAI systems, while understanding the principles of responsible AIWho this book is forThis artificial intelligence book is for aspiring cloud architects, data analysts, cloud developers, data scientists, AI researchers, technical business leaders, and technology evangelists looking to understanding the interplay between GenAI and cloud computing. Some chapters provide a broad overview of GenAI, which are suitable for readers with basic to no prior AI experience, aspiring to harness AI's potential. Other chapters delve into technical concepts that require intermediate data and AI skills. A basic understanding of a cloud ecosystem is required to get the most out of this book.
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Pioneering Applications of Generative AI
Integrating generative artificial intelligence (AI) into art, design, and media presents a double-edged sword. While it offers unprecedented creative possibilities, it raises ethical concerns, challenges traditional workflows, and requires careful regulation. As AI becomes more prevalent in these fields, there is a pressing need for a comprehensive resource that explores the technology's potential and navigates the complex landscape of its implications. The Pioneering Applications of Generative AI is a pioneering book that addresses these challenges head-on. It provides a deep dive into the evolution, ethical considerations, core technologies, and creative applications of generative AI, offering readers a thorough understanding of this transformative technology. By showcasing cutting-edge research and innovative use cases, the book bridges academia and practice, fostering cross-disciplinary collaboration and pushing the boundaries of creativity. Researchers, academicians, scientists, and research scholars will find this book invaluable in navigating the complexities of generative AI in art, design, and media. With its focus on ethical and responsible AI and discussions on regulatory frameworks, the book equips readers with the knowledge and tools needed to harness the full potential of generative AI while ensuring its responsible and ethical use.
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