Search results for "Generative AI System Design"
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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.
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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.
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Generative AI and Stochastic Thermodynamics
Originating from lectures delivered at the African Institute of Mathematical Sciences, this book presents a unifying perspective on traditional and modern methods in generative AI and stochastic thermodynamics. By relating the core topics in machine learning to the notion of (variational) free-energy, a bridge is built between methods such as latent variable models, variational auto-encoders, optimal control, optimal transport, normalizing flows and diffusion models and concepts such as entropy production and fluctuation theorems in stochastic thermodynamics. Structured into three main parts, the book commences by setting up the required mathematical and statistical physics preliminaries needed to make it broadly accessible. The largest part of the book then focuses on building intuition of major advances in generative AI by considering discrete time processes and their relationship to topics in stochastic thermodynamics. Finally, the authors take a short excursion to the continuous time domain for the more advanced learner.
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Generative AI for Full-Stack Development
Gain cutting-edge skills in building a full-stack web application with AI assistance. This book will guide you in creating your own travel application using React and Node.js, with MongoDB as the database, while emphasizing the use of Gen AI platforms like Perplexity.ai and Claude for quicker development and more accurate debugging. The book's step-by-step approach will help you bridge the gap between traditional web development methods and modern AI-assisted techniques, making it both accessible and insightful. It provides valuable lessons on professional web application development practices. By focusing on a practical example, the book offers hands-on experience that mirrors real-world scenarios, equipping you with relevant and in-demand skills that can be easily transferred to other projects. The book emphasizes the principles of responsive design, teaching you how to create web applications that adapt seamlessly to different screen sizes and devices. This includes using fluid grids, media queries, and optimizing layouts for usability across various platforms. You will also learn how to design, manage, and query databases using MongoDB, ensuring you can effectively handle data storage and retrieval in your applications. Most significantly, the book will introduce you to generative AI tools and prompt engineering techniques that can accelerate coding and debugging processes. This modern approach will streamline development workflows and enhance productivity. By the end of this book, you will not only have learned how to create a complete web application from backend to frontend, along with database management, but you will also have gained invaluable associated skills such as using IDEs, version control, and deploying applications efficiently and effectively with AI. What You Will Learn How to build a full-stack web application from scratchHow to use generative AI tools to enhance coding efficiency and streamline the development processHow to create user-friendly interfaces that enhance the overall experience of your web applicationsHow to design, manage, and query databases using MongoDB Who This Book Is For Frontend developers, backend developers, and full-stack developers.
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Learning with Generative Artificial Intelligence
This book delves into the core of education’s digital transformation, presenting a thorough and empirical examination of generative artificial intelligence (GenAI)’s impact beyond the theoretical and fragmented insights prevalent in current discourse.Drawing from peer-reviewed and extensive empirical studies, the contributors aim to unveil the multifaceted effects of GenAI (particularly ChatGPT) on learning. They navigate through topics of interaction, assessment, emotion, effect and efficiency, meta-cognition, and ethics, offering a comprehensive exploration of GenAI’s educational implications. This book presents a closed loop of learning theory, multimodal data, and learning analytics technology. Furthermore, this book builds and proposes core conceptual models for future learning and identifies potential research directions.This book will serve as a foundational reference for educators seeking innovative learning and teaching methods and for researchers and technologists who seek to push the boundaries of educational technology and related areas.
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Practical Guide to Integrating Generative AI into HR Management
This book is a practical guide to the integration of generative AI into human resources, covering use cases across recruitment, onboarding, training, and retention. It offers strategic guidance, ethical frameworks, and technical insights to help organisations deploy generative AI effectively while safeguarding fairness, privacy, and compliance. It covers AI-driven applications in talent acquisition, onboarding, employee engagement, career development, and decision-making, while addressing key concerns such as algorithmic bias, data privacy, and regulatory compliance. With practical case studies and deployment templates, the book provides a structured approach to evaluating and integrating generative AI tools within HR systems. From resume screening to personalised learning paths and predictive analytics, this book bridges the gap between AI technologies and HR operations to help organisations build agile, ethical, and employee-centric workplaces.• Examines generative AI’s applications across recruitment, onboarding, L&D, engagement, and retention• Provides strategic frameworks for integrating AI into HR ecosystems• Includes case studies and practical deployment examples from real organizations• Addresses key issues of AI bias, explainability, data privacy, and compliance• Offers guidance on selecting and evaluating HR-specific AI tools• Explains core AI concepts for both technical and non-technical HR professionals• Includes future-focused insights into AI-driven workforce planning and employee experience designThis book is for HR professionals, business leaders, AI developers, and organizational strategists seeking to understand, implement, and manage generative AI solutions in the HR domain.
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Next-Generation Artificial Intelligence Driven Smart and Renewable Energy
To provide for a sustainable future, the potential synergies at the dynamic intersection of renewable energy (RE) incorporated with smart energy and artificial intelligence (AI) must be exploited. RE is crucial to preserve the environment. Energy involving various systems must be optimized and assessed to provide better performance. However, the design and development of RE systems remains a challenge. Advanced optimization techniques, AI, and machine learning (ML) plays a crucial role in implementing the latest innovative research in the field of renewable energy-integrated electrical systems. This book also describes the practical challenges encountered, and the solutions and future scope to be adopted. Applications of a variety of advanced optimization and AI techniques in the design and development of RE-integrated systems are discussed to provide new solutions in the RE domain.Key features:Discusses modern modeling/control approaches for improving renewable energy integrating artificial intelligence-driven power systemsDescribes the principles and methods of renewable energy generation technologies, and an analysis of their implementation, management, and optimization, and related economic advantagesPresents critical information on the technological design and policy issues that must be taken into considered while implementing a smart gridExplains of the metaheuristic optimization algorithm for complex electrical systems, and the whale optimization algorithm-based multi-objective hydrothermal schedulingCovers the electric vehicle charging station in the distribution network, and transient stability constraint optimal power flow problem using chaotic quasi-oppositional chemical reaction optimizationThe topics covered including microgrids, wind power, solar photo voltaic (PV), optimal power flow (OPF), grid connected inverter, electric vehicle, combined heat and power economic dispatch, FACTS tools for smart energy, harmonic impedance of a salient pole synchronous generator (HI), maximum power point tracking (MPPT) and advanced optimization techniques. Next Generation Artificial Intelligence-Driven Smart and Renewable Energy is ideal for academicians, practitioners, teachers, engineers, industry professionals, researchers, and students in diverse fields, including electrical engineering, electronics and communications engineering, energy, and environmental engineering.
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Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers
The integration of generative AI and deep learning techniques for Alzheimer's disease detection significantly impacts the research community by advancing diagnostic accuracy and providing a comprehensive understanding of the disease. By combining multiple data modalities, including imaging, genetics, and clinical data, researchers can improve diagnostic precision and develop personalized treatment strategies. Generative AI facilitates efficient data utilization through dataset augmentation, fostering innovation and collaboration across interdisciplinary fields. These methodologies forward the exploration of new diagnostic tools while expediting their application in clinical practice, benefiting patients through early detection and intervention. The incorporation of generative AI may enhance research capabilities, promote collaboration, and improve Alzheimer's disease management and patient outcomes. Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers explores the integration of deep generative models in disease diagnosis, biomarking, and prediction. It examines the use of tools like data analysis, natural language processing, and machine learning for effective Alzheimer's research. This book covers topics such as data analysis, biomedicine, and machine learning, and is a useful resource for computer engineers, biologists, scientists, medical professionals, healthcare workers, academicians, and researchers.
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Knowledge Management Systems Design
Knowledge Capital, vital for organizations' sustainability, competitiveness, and stability, can be regenerated in a value-added manner, enabling the development of high-quality products and services through innovative Knowledge Management (KM) techniques. One effective approach is establishing and implementing ISO-compliant Knowledge Management Systems (KMS) across various sectors.Covering nearly all aspects of Knowledge Management, this book offers a comprehensive overview of the evolution and description of core theories, along with their applications in a few case studies that thoroughly analyze the necessary procedures and technologies for developing KMS. The book encompasses the latest trends showcasing the increasing integration of artificial intelligence techniques within KM practices, as discernible through scores of service providers. Additionally, it addresses the challenges of measuring the effectiveness of KM techniques and the value they bring to organizations, thereby supporting the successful and sustainable implementation of KM. It also highlights innovative frameworks such as the Virtuous KM Cycle, MASK techniques, the Daisy Model, and the Husain-Ermine AI-KM Model.The publication is an essential resource for students and researchers specializing in Knowledge Management, as well as for managers, academicians, and practitioners in both the public and private sectors.
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Convergence of Internet of Medical Things (IoMT) and Generative AI
In recent years, the convergence of the Internet of Medical Things (IoMT) and Generative Artificial Intelligence (AI) has revolutionized healthcare delivery, offering unprecedented opportunities to enhance patient care, improve clinical outcomes, and optimize healthcare systems globally. IoMT based smart healthcare system is a collection of several smart medical equipment including wearable devices and apps connected within the network to provide health information. Generative AI revolutionizes global health in areas like medical data synthesis, image enhancement, disease prediction and diagnosis, drug discovery, medical documentation, and personalized healthcare. It offers opportunities to overcome data scarcity and privacy concerns through synthetic data generation and supports accurate disease interpretation and diagnosis through image quality enhancement. However, as IoMT and Generative AI continue to be used across healthcare systems, it is critical to examine their impact on global health, considering diverse socio-economic contexts, cultural sensitivities, and ethical implications. Convergence of Internet of Medical Things (IoMT) and Generative AI explores recent advancements in IoMT and generative AI, with a focus on state-of-the-art approaches, methodologies, and systems for the design, development, deployment, and innovative use of those technologies. It provides insights on how to develop IoMT and generative AI technologies to meet smart business and society development demands, especially in the healthcare field. This book covers topics such as medical technology, wearable technology, and data science, and is a useful resource for medical and healthcare professionals, scientists, engineers, academicians, and researchers.
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Generative AI Unleashed
Today's generative AI has been marked by the advent of neural networks, inspired by the human brain, which are trained to recognize patterns in a dataset. Once the network is trained, it can make decisions or predictions without being programmed to perform tasks. Generative AI learns from a set of data without explicit instructions and can create and generate new digital content such as text, audio and art. Recent models are beginning to overcome challenges such as computational power, data quality and training stability. This edited book on generative AI presents novel perspectives, approaches and methodologies, as well as security, ethical and legal considerations, and future trends. Topics and technologies covered include generative transformers and text generation models, generative models for human-like speech synthesis, generative AI for image synthesis, data synthesis for privacy protection, and exploration of the impact of generative AI in fields including industry 4.0, astronomy, and brain tumour detection. Two chapters offer perspectives on ethics and legality. Generative AI Unleashed: Advancements, transformative applications and future frontiers will serve as a valuable resource for researchers, engineers, advanced students and lecturers operating in the domains that are significantly impacted by generative AI.
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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.
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Communication Skills for Generative AI
Communication Skills for Generative AI: A Practical Guide for Humans is the first comprehensive book to treat communication with generative AI as a distinct human competence—analogous to digital literacy, media literacy, or academic writing skills. Instead of framing the field through the narrow lens of “prompt engineering,” this book introduces a broader, deeper, and more natural paradigm: human–AI communication. It argues that as generative AI becomes embedded in daily life, professional work, research, education, and creative practices, humans must learn not merely to instruct AI systems but to communicate with them effectively, collaboratively, and safely. The book covers the foundations, principles, techniques, and future directions of communicating with modern AI systems. It begins by explaining why the rise of generative AI requires a new set of human capabilities, then outlines the psychological, linguistic, cognitive, and interactional mechanisms that shape human–AI dialogue. It provides a systematic structure of principles (clarity, intent, iteration, cognitive alignment, ethical responsibility) and practical techniques (contextual communication, constraint-based approaches, multimodality, iterative refinement, tone and persona control). The book also examines pitfalls and sources of misunderstanding—such as ambiguity, hallucination, overtrust, and guardrails—and offers strategies for detecting and resolving them. A central contribution of the book is its treatment of collaborative and co-creative communication, where AI is understood not as a passive tool but as an active cognitive partner capable of supporting reasoning, generating ideas, and co-creating text, visuals, and solutions. Another unique perspective is the chapter on metacommunication, which teaches readers how to talk about the communication process itself— expressing preferences, adjusting strategies, and aligning expectations during the dialogue. The book concludes with a forward-looking exploration of the future of AI communication: post-prompting paradigms, persistent personal assistants, intuitive and emotional interfaces, hybrid reasoning models, and the evolving competencies humans will need as AI becomes increasingly autonomous and embedded. This book relates to existing literature on prompt engineering, human–computer interaction, and AI literacy but significantly expands beyond them. While traditional books focus on crafting prompts or operating tools, this work builds a conceptual and methodological foundation for treating AI as a communicative partner. It introduces a unified framework for understanding interaction across text, multimodal interfaces, and emerging real-time systems. This broader perspective positions the book as a pioneering contribution that addresses an urgent gap in current academic, professional, and educational discourse.
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Making Art With Generative AI Tools
In the dynamic realm of generative artificial Intelligence (AI), the fusion of human creativity and machine intelligence has created a vibrant ecosystem of collaborative artmaking. However, this transformative process brings forth a myriad of concerns, ranging from ethical considerations and the need for originality to navigating the legal complexities surrounding intellectual property. As more and more online communities appear around the use of AI to aid in the creation of images, there arises a pressing need for a comprehensive guide that not only dissects the intricacies of artmaking with generative AI tools but also offers practical solutions to the evolving dilemmas faced by artists, researchers, and technologists. Making Art With Generative AI Tools emerges as an exploration of the challenges posed by this intersection of human expression and artificial intelligence. Artists engaging with generative AI find themselves grappling with issues of authenticity, social toxicity, and the commercial viability of their creations. From avoiding stereotypical visuals to ensuring proper crediting, the realm of generative AI is rife with these complexities. Furthermore, the blurred lines between human and machine authorship necessitate a deeper exploration of how these innovative tools impact creativity, representation, and the very fabric of the art world. Tailored for a diverse audience of researchers, artists, and instructional designers, the book navigates through the intricacies of large language models, provides case studies on the usage of generative AIs, and offers practical guidance on creating visuals for storytelling, teaching, and learning. With a keen focus on fostering human creativity, promoting ethical practices, and addressing the legal nuances of this evolving landscape, the book serves as an indispensable compass for those navigating the uncharted waters of artmaking with generative AI tools.
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Integrating AI Techniques into the Design and Development of Smart Cyber-Physical Systems
Building on the knowledge of risks, vulnerabilities, and safety measures associated with cyber-physical systems, this book focuses on adapting artificial intelligence (AI) techniques to smart cyber-physical systems application development. The future is going to see cyber-physical systems in almost every aspect of life, so a book that focuses on shedding light on the design, development, and security aspects of cyber-physical systems in more crucial domains such as defense, healthcare, biomedical, smart city applications, is needed.Integrating AI Techniques into the Design and Development of Smart Cyber-Physical Systems: Defense, Biomedical, Infrastructure, and Transportation offers an introductory exploration of the fundamental theories and concepts of AI and machine learning (ML) that are utilized in the building of dependable cyber-physical systems. It brings the ideas of advanced design and development and empowered security measures to cyber-physical systems. By focusing on the application of AI in cyber-physical systems design as well as security aspects, an improvement in reliability and advancements can be explored. Also included are the latest findings and advancements as well as case studies and illustrative examples on the design and development of smart cyber-physical systems.This resource is highly valuable for those employed in educational institutions, research laboratories, enterprises, and government agencies, as well as for students seeking novel ideas in the realm of smart cyber-physical systems design.
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Generative AI in Higher Education: Ethical Governance, Skills, and Employability
Building upon the foundational principles established in the first volume, this second volume of Generative AI in Higher Education advances the debate on AI beyond theoretical frameworks toward concrete institutional practice. Where the first volume developed guiding principles for higher education institutions to use GenAI effectively and ethically in teaching and learning, this volume introduces original, research-informed frameworks that redefine employability as an ethical, adaptive, and human-centred practice. It presents distinctive models including Skills Dynamics, the Justice–Responsibility Framework for Human Flourishing, and the AI Dialogic Partner frameworks that move decisively from principles to practice.The book integrates ethical governance, curriculum design, and skills formation through actionable models such as the Double ERL Framework (Ethical Regulation Literacy and Ethical Reflexive Learning), the ERL Justice Framework, and the Institutional AI Stewardship Lab (IASL) model. Uniquely combining philosophical depth with policy relevance, it bridges global and local perspectives—drawing on UNESCO, OECD, and regional policy frameworks—to address the ethical, social, and regulatory dimensions of AI in higher education. The volume includes comprehensive international policy analysis, diverse global case studies, and practical tools that transform conceptual exploration into implementable guidance.Generative AI in Higher Education: Ethical Governance, Skills, and Employability serves as essential reading for university leaders, policymakers, educators, and employers seeking to align AI innovation with justice, inclusion, and sustainability. Its practical frameworks and transparency principles empower institutions to position education not merely as a response to technological change but as a transformative force for human flourishing, providing both scholarly contribution and actionable roadmap for embedding ethical AI in higher education practice.
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