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Optimizing Prompt Engineering for Generative AI
In the constantly changing field of artificial intelligence, effective communication and prompt engineering have become essential for developers, researchers, and tech enthusiasts to guide and improve AI. Optimizing Prompt Engineering for Generative AI provides in-depth insight into the techniques and skills needed to create prompts that enhance the performance and relevance of conversational AI systems. Intended for AI practitioners, technology developers, and academics, this book serves as both a foundational text for newcomers and a detailed guide for experienced professionals seeking to refine their skills. This book equips readers with the knowledge to effectively design, test, and refine AI prompts that lead to more accurate, engaging, and ethically aligned AI interactions. From the basics of prompt construction to advanced techniques for specific industries, the content covers a broad spectrum. Each chapter builds on the previous one, starting with an introduction to the fundamental concepts of prompt engineering, moving through detailed discussions on crafting effective prompts, and concluding with insights into future trends and ethical considerations. Through a blend of theoretical explanations, practical applications, case studies, and hands-on exercises, the coverage ensures that readers not only understand the principles of prompt engineering but also know how to apply these principles effectively. By the end of this journey, readers will be equipped to enhance the capabilities of AI systems, making them more responsive, intuitive, and beneficial in a variety of real-world settings. This book is not just a manual; it’s a pathway to mastering the art of conversational AI, designed to foster an innovative approach to AI interactions that are as transformative as they are forward-thinking.
R 912.00
Developer's Guide to AI
A practical, accessible guide that shows working software developers how to integrate real AI features into the applications they already build—using JavaScript, Python, APIs, and modern cloud services, without needing a data-science background.Working developers everywhere now use AI tools, but most still struggle to turn prompts and prototypes into reliable software features. The Developer’s Guide to AI teaches engineers how to build real, maintainable AI capabilities using the tools they already know—JavaScript, Python, APIs, vector search, and simple agent workflows—without advanced math or machine learning.Readers learn where AI belongs in an application, how to design around real-world constraints like latency and cost, and how to avoid the brittle prototypes that fail under changing requirements. With clear examples and production-focused patterns, this book helps developers ship AI features that last.
R 1,607.00
R 305.00
GPT Meets Game Theory
This book explores a new way to understand and employ neural networks through the lens of game theory. It shows how these systems can be seen as players working together or competing to achieve goals. Focusing on transformers, the engines behind today’s most advanced AI, this book explains key mathematical concepts and strategies in a clear, approachable way.As AI models are growing larger and taking on more data, this book draws from biology, physics, as well as game theory, to help readers understand how we can interpret and guide their behavior. It also looks at how these ideas apply to “mean-field” models and how they can be used in situations like federated learning, where many devices work together to train an AI system. The book shows how choosing the right AI design and training method is like making strategic moves in a game - especially when multiple AI agents are involved.This book is an illuminating read for computer science, engineering, and mathematics researchers who are interested in the mathematical underpinnings of deep learning models, particularly transformers, and those who are curious about how game theory can be applied to training and optimizing these models.
R 2,980.94
R 825.00
Generative AI in Writing Education
This book provides a theoretical framework to allow educators, researchers and policymakers to better understand computer-generated writing and the policy and pedagogical implications of generative AI.Generative AI, such as ChatGPT and Gemini, have substantially disrupted educational spaces, forcing educators, policymakers, and other stakeholders to reconsider writing and how it should be used in education. Responding to this disruption, this book provides technically sound guidance on how various stakeholders should engage with generative AI. After providing a foundational and technical discussion of the technology, this book directly addresses the educational context. Informed by theories of learning and knowledge transfer and utilizing rhetorical theories of writing, this book assesses the impact of AI on student learning, student performance and academic honesty and integrity. In doing so, the book outlines how generative AI can be both a help and hindrance for students, enabling readers to craft informed and meaningful policy and successfully integrate AI in the composition classroom.This book will be of interest to scholars in the fields of Rhetoric and Composition, Technical Writing, Communication Studies, Linguistics, TESOL, as well as Education and Machine Learning policymakers, program directors, and researchers.
R 3,598.85
Hands-On Generative Adversarial Networks with Keras
Develop generative models for a variety of real-world use-cases and deploy them to productionKey FeaturesDiscover various GAN architectures using Python and Keras libraryUnderstand how GAN models function with the help of theoretical and practical examplesApply your learnings to become an active contributor to open source GAN applicationsBook DescriptionGenerative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning. This book will be your first step towards understanding GAN architectures and tackling the challenges involved in training them.This book opens with an introduction to deep learning and generative models, and their applications in artificial intelligence (AI). You will then learn how to build, evaluate, and improve your first GAN with the help of easy-to-follow examples. The next few chapters will guide you through training a GAN model to produce and improve high-resolution images. You will also learn how to implement conditional GANs that give you the ability to control characteristics of GAN outputs. You will build on your knowledge further by exploring a new training methodology for progressive growing of GANs. Moving on, you'll gain insights into state-of-the-art models in image synthesis, speech enhancement, and natural language generation using GANs. In addition to this, you'll be able to identify GAN samples with TequilaGAN.By the end of this book, you will be well-versed with the latest advancements in the GAN framework using various examples and datasets, and you will have the skills you need to implement GAN architectures for several tasks and domains, including computer vision, natural language processing (NLP), and audio processing.Foreword by Ting-Chun Wang, Senior Research Scientist, NVIDIAWhat you will learnLearn how GANs work and the advantages and challenges of working with themControl the output of GANs with the help of conditional GANs, using embedding and space manipulationApply GANs to computer vision, NLP, and audio processingUnderstand how to implement progressive growing of GANsUse GANs for image synthesis and speech enhancementExplore the future of GANs in visual and sonic artsImplement pix2pixHD to turn semantic label maps into photorealistic imagesWho this book is forThis book is for machine learning practitioners, deep learning researchers, and AI enthusiasts who are looking for a perfect mix of theory and hands-on content in order to implement GANs using Keras. Working knowledge of Python is expected.
R 1,498.00
R 596.77
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.
R 2,711.00
Generative AI for Cybersecurity and Privacy
Generative AI for Cybersecurity and Privacy offers a groundbreaking exploration of how generative artificial intelligence is reshaping the landscape of cybersecurity and privacy protection in an era of rapid digital transformation. As cyber threats grow in sophistication and scale, this book provides a timely and authoritative guide to harnessing generative AI to safeguard digital ecosystems, secure sensitive data, and address emerging challenges across diverse domains.Spanning a series of expertly curated chapters, this volume delves into cutting-edge advancements and practical applications of generative AI in cybersecurity. It covers critical areas such as AI-driven threat detection and response, privacy-preserving AI models, secure IoT and cloud computing frameworks, and robust defenses for cyber-physical systems, including Smart Cities and wireless networks. The book balances rigorous theoretical foundations with real-world case studies, making it an essential resource for researchers, security professionals, policymakers, and organizational leaders.The book offers comprehensive coverage of key topics, including:• Leveraging generative AI for proactive threat detection, risk analysis, and automated incident response• Innovative approaches to data privacy, compliance, and governance in AI-driven systems• Advanced methodologies for securing IoT, mobile applications, and cloud infrastructures• Practical frameworks for integrating generative AI into cybersecurity strategies for critical infrastructures• Emerging applications of generative AI in personalized, secure digital experiences, such as e-commerce and smart systemsAuthored by a global team of leading researchers and practitioners, this book stands out by not only addressing current cybersecurity and privacy challenges but also proposing forward-thinking, scalable solutions powered by generative AI. Unlike traditional resources, it emphasizes the transformative potential of AI in revolutionizing risk analysis, threat mitigation, and privacy preservation across multiple domains. Whether you’re navigating the complexities of IoT, cloud security, or emerging cyber threats, Generative AI for Cybersecurity and Privacy equips you with the knowledge and tools to build intelligent, secure, and future-ready strategies for a dynamic digital world.
R 5,645.52
Generative AI in Software Development
Generative AI in Software Development: Practical Ways AI is Building the Future of Code explores how large language models and generative tools are fundamentally changing the way software is created, tested, and maintained. This isn’t a theoretical or academic deep dive it’s a practical, grounded guide for developers, product teams, and tech leaders who want to understand how generative AI can be embedded into real-world software workflows. From writing and debugging code to generating UI components, managing APIs, and automating deployment tasks, this book shows how AI is becoming a true co-developer. What sets this book apart is its balance: it's not just for hardcore engineers, nor is it a high-level overview filled with buzzwords. Instead, it sits at the intersection technical enough to be useful, but accessible enough for product managers and decision-makers. The industry is at an inflection point where AI-assisted development is no longer optional; it's becoming essential. This book fills the gap for those who want to move beyond the hype and see exactly how generative AI can speed up development, improve code quality, and change the economics of software delivery.
R 2,308.00
R 7,632.00
Future-Ready with Generative AI
For the first time in history, the most powerful artificial intelligence (AI) works through language itself: The same medium humans use to think and communicate. Dr Michael Kollo reveals why this makes AI uniquely accessible to everyone, and how to harness this linguistic revolution for work and life.This book thoughtfully explores why language-based AI represents something fundamentally different from previous automation, examining both imagined fears and genuine possibilities for workforce transformation. It explains why institutional change takes time despite impressive capabilities, how AI systems are quietly becoming our digital confidants, and why we may eventually come to resent the very technologies we initially embrace. These concepts are explained with care through real-world examples and practical frameworks, whilst companion fictional stories help different audiences understand the emotional reality of technological change. From a software developer orchestrating AI agents to a postal worker finding unexpected digital companionship, these narratives illuminate what it actually feels like to live through this transformation. The book addresses both the remarkable potential of conversational AI and its capacity for subtle manipulation, providing readers with the understanding needed to engage thoughtfully with systems that speak our language.Future-Ready with Generative AI: Skills, Mindsets and Stories in the Age of AI transforms AI from intimidating complexity into intuitive collaboration. Because these systems work through language, everyone can learn to use them effectively. Readers wil gain practical wisdom for leveraging conversational AI while preserving human creativity, relationships, and independent thinking.
R 4,950.00
R 2,015.00
R 465.00
R 489.00
Generative AI on Microsoft Azure
Companies are now moving generative AI projects from the lab to production environments. To support these increasingly sophisticated applications, they're turning to advanced practices such as multiagent architectures and complex code-based frameworks. This practical handbook shows you how to leverage cutting-edge techniques using Microsoft's powerful ecosystem of tools to deploy trustworthy AI systems tailored to your organization's needs. Written for and by AI professionals, Generative AI on Microsoft Azure goes beyond the technical core aspects, examining underlying principles, tools, and practices in depth, from the art of prompt engineering to strategies for fine-tuning models to advanced techniques like retrieval-augmented generation (RAG) and agentic AI. Through real-world case studies and insights from top experts, you'll learn how to harness AI's full potential on Azure, paving the way for groundbreaking solutions and sustainable success in today's AI-driven landscape. Understand the technical foundations of generative AI and how the technology has evolved over the last few yearsImplement advanced GenAI applications using Microsoft services like Azure AI Foundry, Copilot, GitHub Models, Azure Databricks, and Snowflake on AzureLeverage patterns, tools, frameworks, and platforms to customize AI projectsManage, govern, and secure your AI-enabled systems with responsible AI practicesBuild upon expert guidance to avoid common pitfalls, future-proof your applications, and more
R 1,596.00
R 376.00
HBR Guide to Generative AI for Managers
Leverage gen AI to save time, innovate faster, and lead effectively.You're probably aware that generative AI can output quality text and create stunning images in seconds. But smart managers are now using gen AI for high-level work—problem-solving, driving innovation, strategic thinking, and dozens of other applications. Managers who develop their generative AI capabilities will soon be leaping ahead of those who don't. Fortunately, you can start today and see immediate results.The HBR Guide to Generative AI for Managers is packed with practical tips, prompts, and case studies to accelerate and improve countless aspects of your work. You'll learn how to:Run smart experimentsBoost your productivityDetermine the right collaboration mode: a Co-Pilot or a Co-ThinkerDialogue with AI for better decision-makingBe aware of the risks and avoid trapsCapitalize on your gen AI–enabled mindsetArm yourself with the advice you need to succeed on the job, with the most trusted brand in business. Packed with how-to essentials from leading experts, the HBR Guides provide smart answers to your most pressing work challenges.
R 501.00
R 915.00
Generative Adversarial Networks in Practice
Generative Adversarial Networks (GANs) in Practice is an all-inclusive resource that provides a solid foundation on GAN methodologies, their application to real-world projects, and their underlying mathematical and theoretical concepts. Key features: Guides you through the complex world of GANs, demystifying their intricacies. Accompanies your learning journey with real-world examples and practical applications. Navigates the theory behind GANs, presenting it in an accessible and comprehensive way. Simplifies the implementation of GANs using popular deep learning platforms. Introduces various GAN architectures, giving readers a broad view of their applications. Nurture your knowledge of AI with our comprehensive yet accessible content. Practice your skills with numerous case studies and coding examples. Reviews advanced GANs such as DCGAN, CGAN, CycleGAN, and more, with clear explanations and practical examples. Adapts to both beginners and experienced practitioners, with content organized to cater to varying levels of familiarity with GANs. Connects the dots between GAN theory and practice, providing a well-rounded understanding of the subject. Takes you through GAN applications across different data types, highlighting their versatility. Inspires the reader to explore beyond the book, fostering an environment conducive to independent learning and research. Closes the gap between complex GAN methodologies and their practical implementation, allowing readers to directly apply their knowledge. Empowers you with the skills and knowledge needed to confidently use GANs in your projects.Prepare to deep dive into the captivating realm of GANs and experience the power of AI like never before with Generative Adversarial Networks (GANs) in Practice. This book brings together the theory and practical aspects of GANs in a cohesive and accessible manner, making it an essential resource for both beginners and experienced practitioners.
R 4,313.79
Generative AI
The cybersecurity landscape is changing, for sure. For example, one of the oldest threat variants is that of Phishing. It evolved in the early 1990s, but even today it is still being used as a primary threat variant and has now become much more sophisticated, covert, and stealthy in nature. For example, it can be used to launch ransomware, social engineering, and extortion attacks.The advent of Generative AI is making this much worse. For example, a cyberattacker can now use something like ChatGPT to craft the content for Phishing emails that are so convincing that it is almost impossible to tell the difference between what is real and what is fake. This is also clearly evident in the use of deepfakes, where fake images of real people are replicated to create videos to lure unsuspecting victims to a fake website.But, Generative AI can also be used for the good also, to combat Phishing Attacks. This is the topic of this book. In this, we cover the following:A review of PhishingA review of AI, Neural Networks, and Machine LearningA review of Natural Language Processing, Generative AI, and the Digital PersonA proposed solution as to how Generative AI can combat Phishing Attacks, as they relate to Privileged Access accounts
R 6,651.95
Generative AI for Next-Gen Defence Strategies
This book aims to explore the manifold role of Generative AI in enhancing defence capabilities and its potential to transform future warfare. It is divided into three sections. The first discusses the fundamentals of Generative AI and its strategic significance in modern defence sector. This section sets the foundation for understanding how these technologies are shaping current defence strategies and providing a competitive edge. The second explores the application of Generative AI across military, aerospace and naval domain. This section starts by exploring the use of Generative AI for Strategic and Operational Planning, Battlefield Simulation and Training, and development of Autonomous Vehicles and Exoskeletons. The section also covers the use of Generative AI in Drone Swarms, Autonomous Navigation, and Mission Control, as well as its role in maintaining and monitoring Aerospace Infrastructure. Advanced applications such as Radar Systems, Underwater Drones, and Naval Robotics are also discussed in the section. Additionally, the predictive capabilities of Generative AI, including Trajectory Prediction and Failure Prediction for ships and aircraft, and its significance in Naval Warfare and Underwater Sensing have been explored. It also examines the critical role of Generative AI in Cyber Security and Network Defence. The last section of the book addresses the challenges of Generative AI in Defence and the ethical considerations that need to be addressed while using Generative AI in Defence sector. This section also critically assesses the potential threats posed by Generative AI in Cognitive Warfare, highlighting the need for robust ethical frameworks and policies to mitigate risks.The book will be useful for defence professionals, researchers, and technologists who want to understand the transformative potential of Generative AI in defence and attempts to inspire innovative thinking and foster a deeper understanding of the strategic value of Generative AI.
R 6,118.00
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.
R 7,579.25
Generative AI for Software Developers
Master Generative AI in software development with hands-on guidance, from coding and debugging to testing and deployment, using GitHub Copilot, Amazon Q Developer, and OpenAI APIs to build scalable, AI-powered applicationsKey FeaturesHands-on guidance for mastering AI-powered coding, debugging, and deployment with real-world examplesComprehensive coverage of GenAI concepts, prompt engineering, fine-tuning, and SDLC integrationPractical strategies for architecting and scaling production-ready AI-driven applicationsBook DescriptionGenerative AI for Software Developers is your practical guide to mastering AI-powered development and staying ahead in a fast-changing industry. Through a structured, hands-on approach, this book helps you understand, implement, and optimize Generative AI in modern software engineering. From AI-assisted coding, debugging, and documentation to testing, deployment, and system design, it equips you with the skills to integrate AI seamlessly into your workflows.You’ll work with tools such as GitHub Copilot, Amazon Q Developer, and OpenAI APIs while learning strategies for prompt engineering, fine-tuning, and building scalable AI-powered applications. Featuring real-world use cases, best practices, and expert insights, this book bridges the gap between experimenting with AI and production deployment.Whether you’re an aspiring AI developer, experienced engineer, or solutions architect, this guide gives you the clarity, confidence, and tactical knowledge to thrive in the GenAI-driven future of software development. Armed with these insights, you’ll be ready to build, integrate, and scale intelligent solutions that enhance every stage of the software development lifecycle.What you will learnBuild a secure GenAI application with expert guidanceUnderstand the fundamentals of GenAI and its applications in software engineeringAutomate coding tasks with tools like GitHub Copilot, Amazon Q Developer, and OpenAI APIsApply AI for debugging, testing, documentation, and deployment workflowsGet to grips with prompt engineering and fine-tuning techniques to optimize AI outputsImplement best practices for architecting and scaling AI-powered applicationsBuild end-to-end GenAI projects, moving from experimentation to productionWho this book is forThis book is for software developers, engineers, architects, and tech professionals who want to understand the core concepts of Generative AI and its real-world applications, master AI-driven development workflows to improve efficiency and code quality, and leverage tools like GitHub Copilot, Amazon Q Developer, and OpenAI APIs to automate coding tasks.
R 1,791.00
R 1,301.00
Generative Adversarial Networks in Practice
This book is an all-inclusive resource that provides a solid foundation on Generative Adversarial Networks (GAN) methodologies, their application to real-world projects, and their underlying mathematical and theoretical concepts.Key Features: Guides you through the complex world of GANs, demystifying their intricacies Accompanies your learning journey with real-world examples and practical applications Navigates the theory behind GANs, presenting it in an accessible and comprehensive way Simplifies the implementation of GANs using popular deep learning platforms Introduces various GAN architectures, giving readers a broad view of their applications Nurture your knowledge of AI with our comprehensive yet accessible content Practice your skills with numerous case studies and coding examples Reviews advanced GANs, such as DCGAN, cGAN, and CycleGAN, with clear explanations and practical examples Adapts to both beginners and experienced practitioners, with content organized to cater to varying levels of familiarity with GANs Connects the dots between GAN theory and practice, providing a well-rounded understanding of the subject Takes you through GAN applications across different data types, highlighting their versatility Inspires the reader to explore beyond this book, fostering an environment conducive to independent learning and research Closes the gap between complex GAN methodologies and their practical implementation, allowing readers to directly apply their knowledge Empowers you with the skills and knowledge needed to confidently use GANs in your projectsPrepare to deep dive into the captivating realm of GANs and experience the power of AI like never before with Generative Adversarial Networks (GANs) in Practice. This book brings together the theory and practical aspects of GANs in a cohesive and accessible manner, making it an essential resource for both beginners and experienced practitioners.
R 2,408.20
R 7,783.57
R 619.00
R 794.00
R 458.00
Generative Adversarial Networks Cookbook
Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and KerasKey FeaturesUnderstand the common architecture of different types of GANsTrain, optimize, and deploy GAN applications using TensorFlow and KerasBuild generative models with real-world data sets, including 2D and 3D dataBook DescriptionDeveloping Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand.This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use.By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away.What you will learnStructure a GAN architecture in pseudocodeUnderstand the common architecture for each of the GAN models you will buildImplement different GAN architectures in TensorFlow and KerasUse different datasets to enable neural network functionality in GAN modelsCombine different GAN models and learn how to fine-tune themProduce a model that can take 2D images and produce 3D modelsDevelop a GAN to do style transfer with Pix2PixWho this book is forThis book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.
R 1,661.00
R 629.00
GENERATIVE AI AS THE SECOND MIND: REWRITING THE RULES OF BUSINESS AND ORGANIZATION
This book focuses on redefining organizational strategy and management in the era of Generative AI (GenAI). It challenges the foundational assumptions of the Industrial Revolution, arguing that GenAI dissolves the boundaries between labor, materials, and production by introducing a "Second Mind" — a non human entity with human level capabilities and infinite memory. Positioned as workforce, tool, and raw material simultaneously, this paradigm compels leaders to rethink management principles that have guided enterprises for two centuries.The text provides both corporate and academic communities with a rigorous cognitive framework and a strategic roadmap for navigating the transition from legacy hierarchies to symbiotic intelligence. It distinguishes the logic of Classical AI from Generative AI, mapping how each reshapes organizational structures, employee roles, and decision making authority. Central to this framework is the concept of Symbiotic Agency Modes (SAM) — a hierarchy of Coordination, Cooperation, and Collaboration — which specifies how human and digital minds operate as a coupled system.Moving beyond vague "human in the loop" notions, the book introduces actionable governance mechanisms and tailored performance indicators, such as learning rate and reversibility, to evaluate hybrid workforces. By offering a systematic roadmap for implementation, it ensures measurable ROI and sustainable competitive advantage.Serving as an "Origin of Species" for 21st century organizational evolution, this book equips leaders, strategists, and institutions to harness symbiotic intelligence and lead the next era of business transformation.
R 6,521.00
Generation AI
A clear, practical guidebook to being a parent and professional in a world transformed by AI In Generation AI, lifelong entrepreneur, futurist, and consumer trend expert Matt Britton explores how artificial intelligence is reshaping society, from consumer behavior to education, work, relationships, and health. As the first generation born into an AI-enabled world, Generation Alpha will experience a paradigm shift in lifestyle and career paths. Britton examines the unprecedented opportunities AI presents: personalized learning, advancements in healthcare, and automated consumer experiences and processes. Britton also confronts ethical and societal challenges, from privacy issues and economic disparity to the potential impact on mental health and job displacement. Balancing optimism with caution, Britton offers a forward-looking guide for leaders, parents, and individuals on how to navigate a future where AI drives cultural and economic transformation. Generation AI explores timely topics including: Consumer Behavior: AI-driven, personalized shopping and the role of the creator economy in capturing mindshareEducation: Exploring the future of education and the need for learnings to reinvent itself from a curriculum centered on memorization to one focused on problem solving and creativityWork & Career: A deep dive into the AI powered developments driving disruption in the workplace and uncovering the skill sets needed to thriveMental Health & Relationships: Examines AI's potential to both connect and isolate, impacting human interaction.Ethics & Privacy: The need for AI guardrails to protect privacy and ensure fairness amid rapid technological advances. Generation AI is a comprehensive and highly practical guide for all individuals looking to future proof themselves in this brave new world—especially Millennial parents, who are raising the first AI generation, grappling with the disruption of AI in their own lives, and seeking to understand the next stages of our technological evolution.
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