Search results for "Generative AI Infrastructure"
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R 1,527.00

Deep Swarm and Evolution for Generative Artificial Intelligence
This book provides theoretical and practical knowledge about swarm and evolutionary approach of generative AI and Large Language Models (LLMs). The development of such tools contributes to better optimizing methodologies with the integration of several machinelearning and deep learning techniques. In particular, it discusses how the “emergence” concept can contribute to the improvement of AI.The book aims to model human cognitive f unction in terms of “emergence” and to explain the feasibility of AI. To this end, it focuses on human perceptions of “utility.” It describes the emergence of various cognitive errors, and irrational behaviours in the multiobjective situations. It also reviews the cognitive differences and similarities between humans and LLMs. Such studies are important when applying LLMs to real-world tasks that involve human cognition, e.g., financial engineering and market issues.The book describes the intelligent behaviour of living organisms. This is to clarify how to achieve AI in the direction of artificial life. It describes sexual selection, which is a well-known natural phenomenon that troubled Darwin, i.e., why evolutionarily useless items evolved such as peacock feathers and moose antlers etc. The book shows how sexual selection is extended as “novelty search” for the application of generative AI, i.e., the image generation with diffusion model. Real-world applications are emphasised. Empirical examples from real-world data show how the concept of deep swarm and evolution is successfully applied when addressing tasks from such recent fields as robotics, e-commerce Web Shop and image generation etc.
R 2,711.00

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

Return on Intelligence
A call to lead with empathy, this book redefines what transformation means in the age of artificial intelligence. Where most organizations still chase automation and efficiency, Kristin Milchanowski, PhD, reveals a deeper truth: intelligence is not a tool. It is infrastructure. Cutting through the hype and ambiguity that surrounds AI, she bridges the gap between technological deployment and meaningful transformation.Through 43 governing principles, Milchanowski demonstrates how AI agents can reshape decisions, orchestrate resources, and embed permanence into complex enterprises. She introduces two transformative metrics that quantify how well institutions integrate intelligent systems into their workflows and governance. Drawing from global leadership experience, Milchanowski argues that innovation without empathy is merely efficiency without trust. True intelligence must be earned through ethical design, transparent implementation, and human-centered leadership. With precision and moral clarity, she shows how organizations can move from pilots to permanence, from experiments to ecosystems. The real return, Milchanowski concludes, is measured not in algorithms, but in the trust we build, the empathy we embed, and the promises we keep.This book is written for senior executives, transformation leaders, policymakers, and technologists who are navigating the frontier of AI adoption, as well as MBA, AI strategy, and leadership students.
R 9,302.48

Natural Language Processing on Oracle Cloud Infrastructure
This book demonstrates how to use Oracle Cloud Infrastructure (OCI) and Hugging Face technologies to develop advanced NLP solutions. Through a practical case study, it addresses common NLP challenges and offers strategies for creating efficient, cost-effective transformer-based models. By the end of this book, you will have the skills and knowledge to create cutting-edge NLP solutions on OCI, customized to meet the needs of various industries and projects.The book takes you through the complete NLP solution life cycle—covering data preparation, model fine-tuning, deployment, and monitoring—while highlighting key topics such as cost-effectiveness and responsible AI for NLP implementations. Drawing from real-world experience and offering practical insights, it bridges the gap between theory and practice, equipping you to design and deploy scalable, cost-efficient NLP solutions. What You Will LearnMaster key NLP concepts and the OCI ecosystemCreate high-quality datasets using Hugging Face and OCI Data Labeling ServiceFine-tune domain-specific pre-trained models from Hugging Face using OCI Data Science Notebook SessionsDeploy and operationalize your models with OCI Data Science Model DeploymentsAutomate the NLP life cycle with OCI Data Science PipelinesImplement cost-effective strategies throughout the entire NLP life cycle, from dataset preparation to model training and deployment Who This Book Is ForA diverse audience interested in implementing NLP solutions on Oracle Cloud Infrastructure: NLP practitioners, data scientists, and machine learning engineers who want to learn how to leverage Oracle AI and Hugging Face to implement an end-to-end NLP solution life cycle, from data preparation to model deployment; Oracle practitioners who want to expand their Oracle expertise by exploring OCI's advanced capabilities for building and scaling cutting-edge NLP solutions in enterprise environments; business decision makers who want to discover the strategic benefits of NLP solutions on OCI, including cost-effectiveness and responsible AI, while driving business value
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R 2,412.00

Second International Symposium on Generative AI and Education (ISGAIE’2025)
This book presents recent research on generative artificial intelligence (GenAI) and its transformative role in education. It constitutes the proceedings of the Second International Symposium on Generative AI and Education (ISGAIE'2025). The book explores recent advancements in GenAI technologies and their emerging impact on teaching and learning practices across educational contexts. Beyond practical applications and various use cases, the book addresses emerging challenges and opportunities, offering critical reflections on the ethical, pedagogical, and institutional implications of GenAI adoption in education. This book serves as a comprehensive reference for researchers, teachers, education designers, technology developers, and decision-makers who are working to rethink education using generative AI.
R 10,287.89

Generative AI for Business Analytics and Strategic Decision Making in Service Industry
Generative AI is transforming industries by enhancing how businesses analyze data, generate content, and automate complex processes. Its ability to produce diverse, high-quality outputs in areas like marketing, customer engagement, and software development is reshaping productivity and innovation. By leveraging advanced models such as GANs and Transformers, organizations can unlock new insights, streamline decision-making, and personalize services at scale. Generative AI also plays a crucial role in detecting errors, managing knowledge, and mitigating harmful content, contributing to safer and more efficient digital environments. This technology not only accelerates growth but also democratizes access to powerful tools, fostering creativity and problem-solving across sectors. Generative AI for Business Analytics and Strategic Decision Making in Service Industry provides a comprehensive exploration of how generative AI techniques can revolutionize business intelligence and data analytics practices. It offers a detailed examination of innovative algorithms, methodologies, and tools for leveraging generative AI to extract actionable insights, drive innovation, and enhance decision-making processes within the service industry. Covering topics such as big data, generative adversarial networks (GANs), and productivity management, this book is an excellent resource for students, academicians, industry professionals, researchers, managers, and more.
R 7,776.18

Building Tomorrow's Smart Cities With 6G Infrastructure Technology
Emerging technologies such as blockchain, artificial intelligence (AI), digital twins, and advanced internet of things (IoT) sensors are transforming cities into intelligent, interconnected ecosystems through applications such as smart parking, smart healthcare, and smart education. These systems rely on IoT devices and gateways to collect, process, and analyze data for optimizing smart city functions, with advancements shifting from 5G to 6G technology. While these innovations promise to revolutionize urban environments, ensuring security and privacy in 6G infrastructure remains a critical challenge for realizing the full potential of smart cities. Building Tomorrow's Smart Cities With 6G Infrastructure Technology explores the profound impact of emerging technology-enabled secure 6G infrastructure on the creation of futuristic smart cities. It provides relevant theoretical frameworks and the latest empirical research findings. Covering topics such as AI, heritage cities, and web3, this book is an excellent resource for industry professionals, researchers, policymakers, academicians, students, and more.
R 11,053.76

Generative AI with Python and PyTorch
Master GenAI techniques to create images and text using variational autoencoders (VAEs), generative adversarial networks (GANs), LSTMs, and large language models (LLMs)Key FeaturesImplement real-world applications of LLMs and generative AIFine-tune models with PEFT and LoRA to speed up trainingExpand your LLM toolbox with Retrieval Augmented Generation (RAG) techniques, LangChain, and LlamaIndexPurchase of the print or Kindle book includes a free eBook in PDF formatBook DescriptionBecome an expert in Generative AI through immersive, hands-on projects that leverage today’s most powerful models for Natural Language Processing (NLP) and computer vision. Generative AI with Python and PyTorch is your end-to-end guide to creating advanced AI applications, made easy by Raghav Bali, a seasoned data scientist with multiple patents in AI, and Joseph Babcock, a PhD and machine learning expert. Through business-tested approaches, this book simplifies complex GenAI concepts, making learning both accessible and immediately applicable.From NLP to image generation, this second edition explores practical applications and the underlying theories that power these technologies. By integrating the latest advancements in LLMs, it prepares you to design and implement powerful AI systems that transform data into actionable intelligence.You’ll build your versatile LLM toolkit by gaining expertise in GPT-4, LangChain, RLHF, LoRA, RAG, and more. You’ll also explore deep learning techniques for image generation and apply styler transfer using GANs, before advancing to implement CLIP and diffusion models.Whether you’re generating dynamic content or developing complex AI-driven solutions, this book equips you with everything you need to harness the full transformative power of Python and AI.What you will learnGrasp the core concepts and capabilities of LLMsCraft effective prompts using chain-of-thought, ReAct, and prompt query language to guide LLMs toward your desired outputsUnderstand how attention and transformers have changed NLPOptimize your diffusion models by combining them with VAEsBuild text generation pipelines based on LSTMs and LLMsLeverage the power of open-source LLMs, such as Llama and Mistral, for diverse applicationsWho this book is forThis book is for data scientists, machine learning engineers, and software developers seeking practical skills in building generative AI systems. A basic understanding of math and statistics and experience with Python coding is required.
R 1,791.00

Governing Digital Public Infrastructure
This book explores how digital public infrastructures (DPI) should be governed in the public interest, harnessing their potential to drive innovation, inclusion, and societal progress in the age of supercomputers and generative AI.DPI – from hardware and software to data and networks – are becoming increasingly critical to our economy, society, and daily lives. As the AI revolution unfolds, the governance of these infrastructures is coming under scrutiny, with questions arising about how to balance innovation, access, and the public interest. Examining the potential for DPI to empower citizen-entrepreneurs, researchers, small businesses, and the public sector, the book analyses the legal frameworks governing DPI access. Covering key areas such as AI law, data protection, IP law, and competition law, the book emphasizes the need for inclusive and participatory governance models that prioritize transparency, accountability, and the public good. It offers actionable recommendations for policymakers, businesses, civil society, and researchers to collaborate in shaping the future of DPI governance.The book will be of interest to researchers in the field of digital law, digital governance, and public law.
R 9,308.80

Return on Intelligence
A call to lead with empathy, this book redefines what transformation means in the age of artificial intelligence. Where most organizations still chase automation and efficiency, Kristin Milchanowski, PhD, reveals a deeper truth: intelligence is not a tool. It is infrastructure. Cutting through the hype and ambiguity that surrounds AI, she bridges the gap between technological deployment and meaningful transformation.Through 43 governing principles, Milchanowski demonstrates how AI agents can reshape decisions, orchestrate resources, and embed permanence into complex enterprises. She introduces two transformative metrics that quantify how well institutions integrate intelligent systems into their workflows and governance. Drawing from global leadership experience, Milchanowski argues that innovation without empathy is merely efficiency without trust. True intelligence must be earned through ethical design, transparent implementation, and human-centered leadership. With precision and moral clarity, she shows how organizations can move from pilots to permanence, from experiments to ecosystems. The real return, Milchanowski concludes, is measured not in algorithms, but in the trust we build, the empathy we embed, and the promises we keep.This book is written for senior executives, transformation leaders, policymakers, and technologists who are navigating the frontier of AI adoption, as well as MBA, AI strategy, and leadership students.
R 1,954.21


R 611.00



Enterprise Guide for Implementing Generative AI and Agentic AI
Generative AI and Agentic AI together are revolutionizing the technology landscape, with profound and far-reaching impacts across industries. Organizations are increasingly adopting these technologies to drive innovation, enhance unstructured content management, and improve problem-solving capabilities. With Agentic AI, enterprises are moving towards the development of intelligent systems that can plan, reason, and act with autonomy. While early proof-of-concepts (POCs) demonstrated the potential of these technologies, the current shift is toward responsible and scalable production implementations that leverage both generative and agentic capabilities.This book begins by guiding you through the technological evolution of AI, from early machine learning to today's large language models (LLMs) and agentic systems. It then explores a wide range of use cases across industries, highlighting how LLMs can support decision-making, and how Agentic AI enables dynamic, collaborative systems that act with autonomy and intent. This is followed by Design Patterns across the lifecycle of AI solution development, deployment and monitoring. Readers will then gain insights into the methodologies for developing and deploying Generative and Agentic AI solutions at an enterprise level. A featured implementation demonstrates how Agentic AI can be effectively put into action.The book also introduces essential concepts such as MLOps, LLMOps, and Responsible AI principles which are critical for transitioning the AI solutions from experimentation to production. These principles ensure that AI deployments are scalable, secure, ethical and compliant. The book concludes with key takeaways and best practices for developing, evaluating, deploying and scaling AI applications responsibly and effectively within enterprise settings. You Will: Understand key design patterns to develop, deploy and monitor a Generative AI solution effectively.Learn how to develop and implement a production-ready Agentic AI use case.Discover best practices for building scalable, secure, and enterprise-grade AI solutions.Understand how to assess and mitigate risks using Responsible AI principles and LLMOps best practices. This book is for: Enterprise Software Engineers and Architects
R 912.00

R 749.00


Intelligent Urban Infrastructure
Intelligent Urban Infrastructure: Smart Solutions for Sustainable Cities explores how emerging digital technologies are reshaping the design, management, and sustainability of modern cities. This comprehensive volume examines the integration of Artificial Intelligence (AI), Internet of Things (IoT), data analytics, and intelligent automation into critical urban systems such as transportation, energy, water management, healthcare, and public safety. It presents a forward-looking perspective on how infrastructure can evolve to become more adaptive, resilient, and environmentally responsible. The book highlights practical frameworks and technology-driven content that demonstrate measurable improvements in efficiency, cost optimization, and environmental performance. Designed for researchers, postgraduate students, urban planners, engineers, policymakers, and industry professionals, this book serves as a valuable reference for those seeking to understand and implement intelligent infrastructure solutions that enable smarter, greener, and more liveable cities worldwide.
R 9,158.00

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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R 428.00

Generative AI and the Nature of Creativity
Generative AI is now a fact of everyday life, and it is moving into creative domains that were once considered unique to human beings, from painting to composing music and solving complex problems in mathematics. This development raises fundamental questions - What does AI tell us about human creativity? Can it discover new ways of creating art? Can AI become creative independently of humans? If so, what does this imply for the future course of humanity? These questions are explored in this book, which focuses on examining the meaning of creativity as it has been traditionally understood and how AI is changing it.
R 5,862.00

Generative Artificial Intelligence in Higher Education
AsGenerative AI accelerates its impact on the educational landscape, Generative Artificial Intelligence inHigher Education provides a visionary roadmap for universityprofessionals to navigate this transformative era.Throughinspiring case studies, expert analysis, and well-grounded learning theories,this book reveals how Generative AI can empower educators to personaliselearning, promote inclusivity, and elevate pedagogical innovation. At the sametime, it tackles the ethical dilemmas and practical challenges posed byadopting AI, offering actionable strategies for institutions committed toprogress and integrity.Keyhighlights include: Practical insights into integrating AI tools to enhancestudent engagement and learning outcomes – Theoretical frameworks to guide AI’sresponsible and effective use in education – Strategies for institutions toscale AI, improve efficiency, and remain globally competitive. Withcontributions from leading scholars worldwide, this book is a vital resourcefor academics, administrators, and policymakers who aspire to harness AI’spotential while upholding the principles of ethics, equity, and excellence ineducation.Whyshould you read this book? Because AI will transform the future of highereducation. As AI reshapes the academic landscape, this book equips you with theknowledge and tools to lead your institution and students into an innovativeand equitable future. Prepareto engage, inspire, and lead in the AI-enabled academic era.
R 1,720.00

R 611.00

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.
R 1,628.00

Transforming Education With Generative AI
The rise of generative Artificial Intelligence (AI) signifies a momentous stride in the evolution of Large Language Models (LLMs) within the expansive sphere of Natural Language Processing (NLP). This groundbreaking advancement ripples through numerous facets of our existence, with education, AI literacy, and curriculum enhancement emerging as focal points of transformation. Within the pages of Transforming Education With Generative AI: Prompt Engineering and Synthetic Content Creation, readers embark on a journey into the heart of this transformative phenomenon. Generative AI's influence extends deeply into education, touching the lives of educators, administrators, policymakers, and learners alike. Within the pages of this book, we explore the intricate art of prompt engineering, a skill that shapes the quality of AI-generated educational content. As generative AI becomes increasingly accessible, this comprehensive volume empowers its audience, by providing them with the knowledge needed to navigate and harness the potential of this powerful tool. Transforming Education With Generative AI: Prompt Engineering and Synthetic Content Creation offers a comprehensive exploration that delves into an array of topics, from ethical considerations of AI, to inclusivity in education. It further explores personalized learning applications, learning analytics, and cybersecurity in education. Through this in-depth examination, the book reveals how this innovative technology is reshaping the landscape of education in the 21st century, enriching student engagement, and delivering valuable insights into the educational process.
R 9,340.09

Generative AI Security
This book explores the revolutionary intersection of Generative AI (GenAI) and cybersecurity. It presents a comprehensive guide that intertwines theories and practices, aiming to equip cybersecurity professionals, CISOs, AI researchers, developers, architects and college students with an understanding of GenAI’s profound impacts on cybersecurity.The scope of the book ranges from the foundations of GenAI, including underlying principles, advanced architectures, and cutting-edge research, to specific aspects of GenAI security such as data security, model security, application-level security, and the emerging fields of LLMOps and DevSecOps. It explores AI regulations around the globe, ethical considerations, the threat landscape, and privacy preservation. Further, it assesses the transformative potential of GenAI in reshaping the cybersecurity landscape, the ethical implications of using advanced models, and the innovative strategies required to secure GenAI applications. Lastly, the book presents an in-depth analysis of the security challenges and potential solutions specific to GenAI, and a forward-looking view of how it can redefine cybersecurity practices. By addressing these topics, it provides answers to questions on how to secure GenAI applications, as well as vital support with understanding and navigating the complex and ever-evolving regulatory environments, and how to build a resilient GenAI security program.The book offers actionable insights and hands-on resources for anyone engaged in the rapidly evolving world of GenAI and cybersecurity.
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R 305.00

R 519.00

Generative AI with Amazon Bedrock
Become proficient in Amazon Bedrock by taking a hands-on approach to building and scaling generative AI solutions that are robust, secure, and compliant with ethical standardsKey FeaturesLearn the foundations of Amazon Bedrock from experienced AWS Machine Learning Specialist ArchitectsMaster the core techniques to develop and deploy several AI applications at scaleGo beyond writing good prompting techniques and secure scalable frameworks by using advanced tips and tricksPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe concept of generative artificial intelligence has garnered widespread interest, with industries looking to leverage it to innovate and solve business problems. Amazon Bedrock, along with LangChain, simplifies the building and scaling of generative AI applications without needing to manage the infrastructure.Generative AI with Amazon Bedrock takes a practical approach to enabling you to accelerate the development and integration of several generative AI use cases in a seamless manner. You’ll explore techniques such as prompt engineering, retrieval augmentation, fine-tuning generative models, and orchestrating tasks using agents. The chapters take you through real-world scenarios and use cases such as text generation and summarization, image and code generation, and the creation of virtual assistants. The latter part of the book shows you how to effectively monitor and ensure security and privacy in Amazon Bedrock.By the end of this book, you’ll have gained a solid understanding of building and scaling generative AI apps using Amazon Bedrock, along with various architecture patterns and security best practices that will help you solve business problems and drive innovation in your organization.What you will learnExplore the generative AI landscape and foundation models in Amazon BedrockFine-tune generative models to improve their performanceExplore several architecture patterns for different business use casesGain insights into ethical AI practices, model governance, and risk mitigation strategiesEnhance your skills in employing agents to develop intelligence and orchestrate tasksMonitor and understand metrics and Amazon Bedrock model responseExplore various industrial use cases and architectures to solve real-world business problems using RAGStay on top of architectural best practices and industry standardsWho this book is forThis book is for generalist application engineers, solution engineers and architects, technical managers, ML advocates, data engineers, and data scientists looking to either innovate within their organization or solve business use cases using generative AI. A basic understanding of AWS APIs and core AWS services for machine learning is expected.
R 1,465.00


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

R 764.00

Responsible Implementations of Generative AI for Multidisciplinary Use
Generative artificial intelligence (GAI) represents a profound leap in technological advancement, empowering machines to create content that closely mimics human creativity in various forms. As this technology continues to evolve and permeate multiple industries, it is essential to address the accompanying ethical considerations that arise from its use. Furthermore, there is a need for transparency in how GAI systems are developed and deployed to ensure that they are used responsibly and that their outputs are reliable and fair. Balancing innovation with ethical practices will be crucial to harnessing the benefits of GAI while mitigating its risks and ensuring its positive contribution to society. Responsible Implementations of Generative AI for Multidisciplinary Use highlights both the immense potential of GAI and the ethical challenges it presents. This book demystifies GAI by breaking down complex concepts into accessible language and offering real-world examples that illustrate the implications of its applications. Covering topics such as chatbots, ethical leadership, and the metaverse, this book is an excellent resource for technology professionals and developers, ethicists, policymakers, academicians, researchers, business leaders and executives, legal experts, students, educators, and more.
R 10,636.53

Proceedings of International Conference on Generative AI, Cryptography and Predictive Analytics
The book presents the proceedings of the International Conference on Generative AI, Cryptography and Predictive Analytics (ICGCPA 2024), held at VIPS-TC, School of Engineering and Technology, Pitampura, Delhi, India, during June 28 – 29, 2024. It covers Generative AI's role in problem-solving, examining applications in image synthesis, content creation, healthcare, and optimization challenges. This book is a valuable resource for postgraduate students in various engineering disciplines.
R 12,523.78

R 1,780.00

Generative AI Tools
Generative AI algorithms have become transformative forces in today's digital landscape, revolutionizing industries from healthcare and finance to creative arts and software development by enabling machines to create human-like content, automate complex tasks, and generate innovative solutions at unprecedented scale and speed. These applications are driving significant productivity gains across organizations, with AI-powered tools like large language models, image generators, and code assistants helping professionals streamline workflows, enhance creativity, and solve problems that were previously time-intensive or required specialized expertise. The strategic importance of generative AI extends beyond operational efficiency, as it represents a fundamental shift toward intelligent automation that is reshaping competitive advantages, creating new business models, and establishing AI literacy as a critical skill for future workforce success. Generative AI Tools: From Algorithms to Applications is a reference for researchers that consolidates rapidly evolving methodologies, theoretical foundations, and practical implementations. Highlights include:Generative AI tools and the marketing industryA comprehensive overview of ChatGPTChatGPT integration in IoT ecosystemsProviding a structured framework for understanding this complex and fast-moving field, the book enables researchers to build upon established knowledge more efficiently, avoid redundant work, and identify promising research directions by offering systematic coverage of current state-of-the-art techniques, their limitations, and emerging challenges that require innovative solutions. Bridging the gap between theoretical concepts and real-world applications, the book helps researchers understand not only how these algorithms work but also their practical implications, ethical considerations, and potential societal impacts, which is crucial for developing responsible and impactful AI research agendas.
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