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R 1,921.00
Generative AI for Academics
This is your indispensable guide to navigating the rise of generative AI as an academic. It thoughtfully explores rapidly evolving AI capabilities reshaping higher education, examining challenges and ethical dilemmas across the sector.It provides useful strategies for using generative AI in your scholarly work while upholding professional standards. This practical guidance addresses four core areas of academic work:Thinking: How to use generative AI to augment individual and collaborative scholarly thinking that can assist in developing novel ideas and advancing impactful projectsCollaborating: Explore how generative AI can be used as a research assistant, coordinating teams and enhancing scholarly cooperationCommunicating: Cautioning against over-reliance, examine how generative AI can relieve communication burdens while maintaining professionalism and etiquetteEngaging: thoughtful and practical frameworks are offered for using these developments to support online engagement without sacrificing scholarly principlesMark Carrigan is a digital sociologist, author and Lecturer in Education at the University of Manchester.
R 1,408.00
Empowering the Public Sector with Generative AI
This is your guide book to Generative AI (GenAI) and its application in addressing real-world challenges within the public sector. The book addresses a range of topics from GenAI concepts and strategy to public sector use cases, architecture patterns, and implementation best practices. With a general background in technology and the public sector, you will be able to understand the concepts in this book.The book will help you develop a deeper understanding of GenAI and learn how GenAI differs from traditional AI. You will explore best practices such as prompt engineering, and fine-tuning, and architectural patterns such as Retrieval Augmented Generation (RAG). And you will discover specific nuances, considerations, and strategies for implementation in a public sector organization. You will understand how to apply these concepts in a public sector setting and address industry-specific challenges and problems by studying a variety of use cases included in the book in the areas of content generation, chatbots, summarization, and program management. What You Will LearnGenAI concepts and how GenAI differs from traditional AI/ML Prompt engineering, fine-tuning, RAG, and customizing foundation modelsStrategy, methodologies, and frameworks for the public sectorPublic sector use cases in the areas of content generation, summarization, and chatbots, plus program management, analytics, business intelligence, and reportingArchitecture and design patterns Implementation, operations, and maintenance of GenAI applications Who This Book Is ForTechnology and business leaders in the public sector who are new to AI/ML and are keen on exploring and harnessing the potential of Generative AI in their respective organizations.
R 1,140.00
Gen AI-assisted Agile Course, Project-Based Teaching and Learning
This title represents an essential resource for understanding the evolving landscape of AI-augmented pedagogy, examining the transformative effects of generative artificial intelligence (GenAI) on education through the lens of agile course design and project-based learning.Through a detailed analysis of diverse empirical case studies from eight countries between 2015 and 2024, the authors effectively illustrate the dual impact of GenAI on education, academic integrity, and teacher autonomy. They demonstrate how GenAI can enhance personalized STEM education and STREAM (Science, Technology, Reading and Writing, Engineering, Arts and Mathematics) instruction, as well as project-based learning, while simultaneously presenting significant challenges. They provide a nuanced assessment of the opportunities and disruptions introduced by GenAI and offer concrete pedagogical strategies for teaching practitioners.This book serves as a vital reference for scholars in GenAI, educational technology and curriculum, and instruction. It also provides practical, ready-to-implement pedagogical approaches for pre-service teachers in higher education and primary and secondary schools.
R 9,298.36
Provoking Generative AI Futures
An accessible exploration of the myriad applications and challenges of generative AI for media and communication students, scholars, and practitioners alike.The latest emergence of increasingly low-cost and scalable AI technologies presents a point of both celebration and concern for the contemporary media and information ecosystem. To this end, this edited volume gathers media and communications scholars and practitioners to engage in discussions and exchange ideas about current trends and developments in the field. Questions this volume asks include: What are the essentials of generative AI from a media and communication perspective? How has generative AI influenced research and scholarship? How has generative AI influenced media content and industries? What ethical and legal questions has generative AI introduced or reignited? How are discussions of generative AI influencing perception of the technologies? Who benefits from generative AI, and who might be disenfranchised? As generative AI develops at a rapid pace, this collection provides a calibration point for further discussion and debate around their role in media and communication.This book will appeal to students seeking to gain greater understanding of generative AI within the media and communication industries, as well as media and communication scholars and practitioners directly engaged in generative AI research, application, and development.
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Generative Intelligence in Healthcare
This book explores the intersection of artificial intelligence and healthcare with a focus on generative intelligence. The book will introduce the concept of generative intelligence and its transformative potential in patient care, showcasing applications that go beyond conventional AI approaches.Generative Intelligence in Healthcare: Transforming Patient Care with AI Creativity delves into the use of generative models for personalized medicine, data analytics, and predictive modelling, providing real-world examples of how AI creativity can revolutionize treatment strategies and diagnostic processes. It focuses on the origin and basics of generative AI, generative AI models, and possible areas in healthcare where generative AI can work. It discusses how generative AI model will help healthcare providers automatically generate prescriptions, discharge summaries, and patient conditions. The unique strength of this book lies in its comprehensive examination of ethical considerations and regulatory frameworks, ensuring a responsible and transparent integration of generative intelligence in healthcare. By addressing current challenges and envisioning future directions, this book serves as a valuable resource for healthcare professionals, researchers, and policymakers seeking to harness the full potential of AI creativity to enhance patient outcomes.The book is written for graduate students, researchers, and professionals in biomedical engineering, electrical engineering, signal process engineering, biomedical imaging, and computer science.
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Fairness in Generative AI
Build responsible AI systems with practical fairness benchmarks. Turn fairness principles into measurable requirements using metrics, human review, AI governance, CI gates, and drift monitoring across text, image, and multimodal AI.Key FeaturesTurn generative AI fairness principles into testable responsible AI requirementsBuild benchmarks and metrics for LLMs, image models, and multimodal generative AIOperationalize AI governance with human review, CI gates, drift monitoring, and scorecardsApply AI ethics to identify harms, evaluate trade-offs, and guide model releasesBook DescriptionA child asks an image model for a picture of a soccer player and gets a boy, every time. Across hiring, lending, education, and healthcare, fairness in generative AI can affect opportunity, dignity, and trust. This practical guide shows you how to measure fairness and build responsible AI practices across LLMs, image models, and multimodal generative AI systems.Move from AI ethics and fairness principles to engineering artifacts you can test and defend. Define harms and sensitive attributes, decide whose experience is in scope, and translate fairness trade-offs into measurable requirements. Then build a modular benchmarking framework for your ML and MLOps pipelines using versioned scenario and prompt libraries, quantitative metrics, qualitative rubrics, and human review.Put AI governance into practice by publishing actionable scorecards and dashboards, adding fairness checks to CI and release gates, monitoring drift, and preparing incident-response playbooks. Keep evaluation meaningful as models, data, and expectations change.A running soccer image-generator case connects the concepts to implementation, showing how responsible AI engineering moves from principles to measurable production controls.What you will learnTurn fairness principles into testable requirements for generative AIMap harms to representational, allocative, and procedural checksDesign versioned scenario and prompt libraries that protect real dataImplement fairness metrics for text, image, and multimodal AI outputsApply human review with rater training and inter-rater agreementPublish scorecards and dashboards stakeholders can act onGate model releases on fairness and monitor drift in productionRun incident-response playbooks that keep benchmarks credibleWho this book is forThis book is for people who build, ship, evaluate, and govern generative AI. ML and data engineers, application developers shipping LLM features, and responsible AI, trust-and-safety, and security engineers will gain hands-on value. Product managers and engineering leaders will develop a shared language for AI governance, while policymakers, regulators, researchers, standards contributors, and civil-society advocates will find structured ways to scrutinize deployed systems. A working grasp of ML evaluation and Python is all you need.
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Multimodal Generative AI in the Enterprise: From Pixels to Profit
Build and deploy enterprise-grade multimodal AI systems using generative models for text, image, audio, and video.Key FeaturesDesign end-to-end multimodal AI systems for enterprise workloadsBuild scalable pipelines using Gemini, Veo, Imagen, Airflow, and KubeflowImplement governance, safety, and compliance for AI-generated contentPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe Multimodal AI Playbook equips enterprise developers and ML engineers with the practical skills needed to build real-world generative systems using text, image, audio, and video models. This book offers a complete stack approach—starting from theory and progressing through tooling, orchestration, governance, and full-scale deployment.Beginning with the foundations of multimodal learning and generative AI models, you’ll explore how to generate modality-specific content while navigating key trade-offs in model selection, scalability, and orchestration. With a dedicated focus on enterprise use cases like automated marketing campaigns, the book shows how to manage model outputs responsibly covering bias detection, IP risk, and content safety.You'll implement a full pipeline using enterprise-ready models such as Gemini, Veo, and Imagen. With forward-looking chapters on real-time generation, 3D assets, and multimodal agents, this book bridges the gap between technical mastery and business impact- preparing you to lead in the AI-first future. What you will learnDesign full-stack multimodal AI architecturesGenerate text, image, audio, and video contentBuild automated AI-powered marketing workflowsCompare and fine-tune leading multimodal modelsDeploy AI pipelines with Airflow and KubeflowImplement AI safety, governance, and complianceCreate real-time and 3D multimodal experiencesIntegrate AI with enterprise cloud platformsWho this book is forSoftware engineers, ML engineers, data scientists, technical product managers, and solution architects looking to build and deploy multimodal generative AI systems in production. Professionals familiar with Python, machine learning concepts, and cloud platforms such as AWS, Azure, or GCP will gain practical guidance for implementing scalable, enterprise-ready AI solutions.
R 1,628.00
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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Scaling Generative AI
This book contains the operational readiness framework, providing step-by-step guidance to enterprises to prepare themselves for the scaled adoption of generative AI. Different enterprises have reacted differently to the generative AI hype. The real value of generative AI lies in the scaled adoption. Only 10 percent of the enterprises have been able to scale. A staggering 90 percent of them are lagging. This has caused a "huge gap" between the scaling and lagging firms. Closing this huge gap is a daunting task.To bridge this gap, enterprises must be operationally ready in the following four areas:CustomerTechnologyDataPeopleThis book contains the operational readiness framework, providing step-by-step guidance to enterprises to prepare themselves for the scaled adoption of generative AI.Although the framework is primarily for the executives, leaders, managers, consultants, strategists, and transformation drivers at the lagging firms, the scaling firms can use it to assess their current operational readiness levels and mitigate the prevailing gaps. It can also provide useful insights to the entrepreneurs in the generative AI value chain to develop unique solutions. Additionally, it can help technology and management students to align themselves better to embrace new challenges of the corporate world they will soon enter.The success of this book lies in how effectively the readers apply the framework at their workplace. This book is not just about information…it's all about transformation!
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Generative AI in Creative Industries
This book compiles a comprehensive collection of pioneering research that addresses the multifaceted challenges and theoretical aspects of Generative AI in creative industries. Generative AI, a groundbreaking technological development, has been carving a significant niche within the creative industries. This innovative form of AI, exemplified by models like OpenAI's ChatGPT, is not only transforming the landscape of human-like text generation but is also radically reshaping creative fields such as music, literature, and visual arts. In the realm of creative industries, Generative AI serves as a catalyst for artistic innovation, offering tools for artists to push the boundaries of creativity. It assists in composing music, generating unique artworks, and even writing stories or scripts, thereby democratizing the creative process. The integration of Generative AI in these industries promises a synergy between human creativity and machine intelligence, potentially leading to novel genres and forms of art. Despite its transformative potential, the incorporation of Generative AI in creative fields is not devoid of challenges. Ethical considerations, such as authorship rights, originality, and the impact on traditional creative roles, are pivotal. Moreover, the authenticity and emotional depth of AI-generated content compared to human-created art is a subject of ongoing debate. The book aims to feature original manuscripts encompassing a wide array of topics, from the development of new generative technologies and their practical application in creative fields, to critical analysis of the ethical, legal, and cultural implications of these systems. By gathering the latest advancements in this field and spotlighting emerging avenues for research, this book serves as an invaluable resource and guide for researchers, artists, and practitioners operating at the intersection of Generative AI and creative industries.
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E-Business. Generative Artificial Intelligence and Management Transformation
The three-volume set LNBIP 549 - 551 constitutes the refereed proceedings of the 24th Wuhan International Conference on E-Business, WHICEB 2025, which was held in Guangzhou, China, during June 6-8, 2025. The total of 92 papers included in the proceedings was carefully reviewed and selected from 324 submissions. The papers have been organized in topical sections as follows: Part I: Artificial Intelligence and New Ways of Working; Conversational Artificial Intelligence and Information Behavior; Data Analytics and Digital Governance; Data Intelligence and Social Computing on Digital Platforms; Digital Enablement and Digital Governance; Digital Innovation and Social Impact;Part II: Digital Technologies for Sustainable Development; Disruptive Technologies and Digital Transformation; E-business Strategy and Online Marketing; Emerging e-Commerce Initiatives Enables by Advanced Technologies; Engaging Technologies; Part III: Generative AI-enhanced Risk Analytics and Modelling; Healthcare Service and IT Management; Human-AI Integration in Organizations; Next-Gen Technologies and Social Commerce; Privacy and Security in Artificial Intelligence Generated Content; Transformative Digital Innovations: Education, Sports, and Entertainment; and General IS and Digital Business Topics.
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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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Genai on Google Cloud
In today's AI landscape, success depends not just on using large language models but on moving them into production in a way that's scalable, compliant, and cost-effective. GenAI on Google Cloud: Enterprise Generative AI Systems and Agents is your hands-on guide to bridging that gap. Whether you're an ML engineer tackling your first multi-agent application or a product leader responsible for scaling a GenAI strategy, this book offers a practical game plan for taking your LLM applications from promising prototype to enterprise-grade solution. Written by practitioners with deep experience in MLOps, data engineering, and GenAI infrastructure, this guide takes you through real-world workflows using Google Cloud's Vertex AI--from training and deployment to monitoring and integration. With concrete examples, field-tested frameworks, and honest insights about what actually works, you'll learn how to build production systems that deliver measurable business value. Bridge the prototype-to-production chasm that stalls 75% of LLM projects using systematic frameworks developed across hundreds of deploymentsNavigate the unique complexities of LLM operations through practical guidance on data orchestration, evaluation frameworks, and responsible AI practicesBuild enterprise-grade multimodal systems that handle text, images, and video with robust agent architectures and tool integrationImplement proven optimization strategies for cost management, performance tuning, and production monitoring at scaleApply battle-tested patterns from practitioners who've guided organizations through both breakthrough successes and costly failures
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Generative AI for a Net-Zero Economy
This book covers the technological aspects of Generative AI, its applications in achieving a net-zero carbon economy, the challenges of climate change, and the economic and management implications of these transitions. The book explores the transformative potential of Generative AI in driving the transition to a net-zero economy. It examines how this cutting-edge technology is revolutionizing climate change mitigation strategies and reshaping business models in the digital age. The book offers a comprehensive guide to leveraging AI for sustainable innovation through case studies, expert insights, and forward-thinking analysis. It addresses the challenges and opportunities in integrating AI into climate action plans, economic policies, and corporate strategies. Essential reading for policymakers, business leaders, and technologists, this book provides a roadmap for harnessing Generative AI to create a sustainable, prosperous future encompassing several key elements that align with the United Nations Sustainable Development Goals, in particular SDG 13: Climate Action.
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Generative AI, Media, and Society
This groundbreaking book demystifies generative AI’s transformative impact on media, socio-cultural dynamics, ethics, and policy.Defining generative AI as an evolutionary leap in the development of artificial intelligence, the author examines intricate human-machine interactions and socio-technical dynamics, advocating robust, proactive AI governance to address emerging uncertainties. The book is clearly structured into six key chapters, each exploring distinct aspects of the relationship between artificial intelligence, media, and society. The chapter on "Transformation" examines how machine behavior is reshaping our datafied society, questioning whether data is the new oil, or digital manure. "Generative AI" investigates the models and future impacts of generative AI as a co-intelligence, revisiting the Turing Test and analyzing societal-business impacts. "AI Media" explores the convergence of media and AI, highlighting robot journalism, synthetic content, and the disinformation era and discussing the trend toward high-risk optimism. "Uncertainties" addresses inherent unpredictability vs. strategic foresight, focusing on challenged business models, sustainability concerns, and emotional intelligence factors. "Ethics" analyzes generative morality and dual-use technology, covering trusted AI principles—from misuse to integrative solutions. Finally, "Policy" discusses governance, labor market impacts, and the importance of human rights and power dynamics in generative AI. Each chapter also provides summaries of impact projects, reflective art, scholarly questions, and strategic takeaways—extended with a comprehensive glossary.This is an essential resource for scholars, students, policymakers, technologists, ethicists, and AI industry leaders seeking to rapidly understand and address the challenges and opportunities of generative AI and AI media in a cohesive framework.
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Generative AI for Leaders Playbook
Lead the AI revolution with confidence. Learn how to craft strategy, build AI teams, and drive innovation responsibly with this practical leadership playbook for the Generative AI era.Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild AI fluency and lead digital transformation with confidenceDesign enterprise-wide AI strategy, teams, and governance modelsUnlock growth with responsible and scalable Generative AI adoptionBook DescriptionGenerative AI has shifted from a technical breakthrough to a leadership imperative. This essential guide helps executives, directors, and tech leads navigate the transformation, bridging AI’s technical realities with enterprise applications and providing the frameworks and vocabulary needed to make informed decisions.Written for strategic leaders and decision-makers, this practical playbook demystifies key concepts, including generative AI, large language models (LLMs), and emerging agentic AI systems. It shows you how to develop AI strategies aligned with business goals, build AI-first organizations, and establish governance frameworks for responsible, compliant adoption. Real-world examples show how leading companies use AI to drive innovation, efficiency, and growth.Beyond strategy, you’ll learn how to build and scale AI teams, evaluate technology vendors, and integrate AI across business functions. You’ll also explore global policy trends, ethical implications, and the governance frameworks emerging across jurisdictions.This playbook provides a roadmap for turning AI disruption into sustainable competitive advantage, equipping executives with the strategic understanding and practical guidance needed to lead, implement, and scale AI responsibly.*Email sign-up and proof of purchase requiredWhat you will learnUnderstand generative and agentic AI capabilities and business valueBuild organizational AI literacy and cultural readinessCraft an enterprise AI strategy aligned with business goalsDesign and scale high-performing AI teams and structuresEvaluate AI platforms and vendors for transparency and reliabilityEmbed responsible AI governance and compliance frameworksWho this book is forThis book is for AI professionals, AI business leaders, founders, and senior managers who need to navigate the strategic, operational, and ethical challenges of AI adoption. It’s also invaluable for consultants, policy leaders, and transformation specialists advising enterprises on AI readiness. No coding knowledge is required—only a vision to lead AI-powered change across industries.
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Generative AI in Higher Education
Chan 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.
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Integration Strategies of Generative AI in Higher Education
Amidst the rapid evolution of educational technology, a pressing challenge confronts higher education institutions: how to effectively integrate generative artificial intelligence (AI) into their existing frameworks. As universities strive to adapt to the digital age, they are met with the complexities of incorporating AI-driven solutions to enhance teaching, learning, and administrative processes. However, the lack of comprehensive strategies and guidance hinders their ability to leverage AI's full potential, leaving educators and administrators grappling with uncertainty. In response to this critical dilemma, Integration Strategies of Generative AI in Higher Education emerges as a guide for clarity and innovation. By offering methodological insights and practical frameworks, this book equips higher education stakeholders with the tools needed to navigate the intricacies of AI integration. From curriculum enhancement to AI-driven content creation, the book provides actionable strategies tailored to the unique needs and challenges of higher education institutions. As educators, administrators, and policymakers seek to harness the transformative power of AI in education, this book serves as an indispensable roadmap for success. By synthesizing best practices from diverse educational contexts and addressing key considerations such as regulatory frameworks and ethical implications, this book empowers stakeholders to embrace AI with confidence, ushering in a new era of innovation and excellence in higher education.
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