Allgemein
AI Trust, Risk, and Security Management
For industry practitioners, academic researchers, and governance professionals alike, this book offers both clarity and depth in one of the most important domains of modern technology. As AI matures, trust and risk management will define its success—and this book lays the groundwork for achieving that vision. As AI continues to permeate sectors ranging from healthcare to finance, ensuring that these systems are not only powerful but also accountable, transparent, and secure, is more critical than ever. This book offers a vital exploration into the intersection of trustworthiness, risk mitigation, and security governance in artificial intelligence systems, serving as a definitive guide for professionals, researchers, and policymakers striving to build, deploy, and manage AI responsibly in high-stakes environments. Using a comprehensive approach, it explores how to integrate technical safeguards, organizational practices, and regulatory alignment to manage the unique risks posed by AI, including algorithmic bias, data misuse, adversarial attacks, and opaque decision-making. The result is a strategic approach that not only identifies vulnerabilities, but also promotes resilient, auditable, and trustworthy AI ecosystems. At its core, AI TRiSM is a forward-looking concept that embraces the realities of AI in production environments. The framework moves beyond traditional static models of governance to propose dynamic, adaptive controls that evolve alongside AI systems. Through real-world case studies, the book outlines how tools like model cards, bias audits, and zero-trust architectures can be embedded into the AI development lifecycle. Readers will find the volume: Introduces concepts to stay ahead of regulations and build trustworthy AI systems that customers and stakeholders can rely on;Addresses security threats, bias, and compliance gaps to avoid costly AI failures;Explores proven frameworks and best practices to deploy AI responsibly and strategies to outperform;Provides comprehensive guidance through real-world case studies and contributions from industry and academia. Audience AI and machine learning engineers, data scientists, cybersecurity and risk management specialists, academics, researchers, and policymakers specializing in AI ethics, security, and risk management. R. Karthick Manoj, PhD is an Assistant Professor at the Academy of Maritime Education and Training Tamil Nadu, India, with more than 14 years of experience. His scholarly contributions include six national and twelve international journal articles, four patents, three books, ten book chapters, and more than fifteen conference presentations. S. Senthilnathan, PhD is an Assistant Professor in the Department of Electronics and Communication Engineering in the School of Engineering and Technology at Christ University, Bangalore, India. His research interests include quantum dot cellular automata and quantum computing. S. Arunmozhi Selvi, PhD is a Professor in the Holy Cross Engineering College, Anna University, Tamil Nadu, India with more than 15 years of research and teaching experience. She has published 30 articles in international journals and conference proceedings and written many book chapters. T. Ananth Kumar, PhD is an Associate Professor in the Department of and Computer Science and Engineering, IFET College of Engineering, Tamil Nadu, India. He has authored one book, edited six books and several book chapters, and presented papers in various national and international journals and conferences. S. Balamurugan, PhD is the Director of Research at iRCS, an Indian Technological Research and Consulting, Coimbatore India. He has published 100 books, 300 papers in international journals and conferences, and 300 patents. With 20 years of experience researching various cutting-edge technologies, he provides expert guidance in technology forecasting and decision making for leading companies and startups.
Quantum Computing and Machine Learning for 6G
Secure your expertise in the next frontier of wireless technology with this essential book, which provides a deep dive into the integration of machine learning and quantum computing to build the necessary infrastructure for 6G communication networks. Despite the potential benefits of 6G, the technology to enable its realization is not yet available. As a result, the development of technology to solve these challenges must be met before we can start working towards 6G. The primary applications of machine learning within 6G are to create necessary infrastructure advantages as the technology matures. Additionally, 6G communication networks use quantum computing to detect, mitigate, and prevent security vulnerabilities. By integrating machine learning and quantum computing into 5G and 6G technology, intelligent base stations will be able to make decisions for themselves, and mobile devices will be able to create dynamically adaptable clusters based on learned data. This book highlights the role of real-time network learning and the integration of quantum computing, machine learning, and quantum machine learning to enhance service quality. It provides a deep dive into the interplay of these technologies within 6G networks, starting from 5G fundamentals. The book elaborates on how these advanced technologies will underpin 6G’s architecture to meet comprehensive service demands, including those for smart city applications requiring extensive coverage, ultra-low latency, and reliable connectivity. The book details how the synergy between quantum computing, machine learning, and 6G technologies will transform communications, revolutionize markets, and enable groundbreaking applications globally. Readers will find the volume: Explores real-world scenarios for illustrating the integration of quantum computing and machine learning in 6G;Covers an extensive range of applications to illustrate the full picture of 6G that implements machine learning and quantum computing approaches;Offers expert insights through a comprehensive collection of literature reviews and research articles;Introduces the interdisciplinary innovations and potential of 6G across multiple industries. Audience Scientists, industry professionals, researchers, academicians, instructors, and students working in quantum computing and machine learning, especially in the context of advanced wireless communication technology. Pallavi Sapkale, PhD is an Assistant Professor, Ramrao Adik Institute of Technology, D.Y. Patil University, Navi Mumbai, Maharashtra, India, with more than 17 years of experience. She has published four books, more than 25 research articles in various international journals and conferences, four international patents, and 12 Indian patents. Her research focuses on quantum computing, machine learning, wireless communication, 5G mobility management, and next-generation networks like 6G. Shilpa Mehta, PhD is a Teaching Assistant at the Auckland University of Technology, New Zealand, with more than five years of teaching experience. She has worked on various interdisciplinary research projects and edited several internationally published books. Her research interests include radio frequency integrated circuits, RF front ends, optimization, Internet of Things, wireless communication, artificial intelligence, healthcare, radars, and smart cities. S. Balamurugan, PhD is the Director of Albert Einstein Engineering and Research Labs, Coimbatore, Tamilnadu, India. He has published more than 60 books, 300 articles in national and international journals and conferences, and 200 patents. He is also the Vice-Chairman of Renewable Energy Society of India (RESI). He also serves as a research consultant for many companies, startups, and micro-, small, and medium enterprises.
Generative Artificial Intelligence for Next-Generation Security Paradigms
Fortify your digital defenses with this essential book, which provides a roadmap for moving beyond the limitations of traditional encryption by leveraging generative AI algorithms to proactively anticipate, detect, and mitigate the next generation of cyber threats in real-time. In recent years, encryption has shown limitations as the sole safeguard against cyber threats in an increasingly interconnected world. While encryption remains a crucial component of cybersecurity, it is no longer sufficient to combat the evolving tactics of malicious actors. This book advocates for a paradigm shift towards leveraging generative AI algorithms to anticipate, detect, and mitigate emerging threats in real-time. Through detailed case studies and practical examples, the book illustrates how these AI-driven approaches can augment traditional security measures, providing organizations with a proactive defense against cyberattacks. It explores the connections between artificial intelligence and cybersecurity, exploring how generative AI technologies can revolutionize security paradigms beyond traditional encryption methods. Authored by leading experts in both AI and cybersecurity, the book presents a comprehensive examination of the challenges facing modern digital security and proposes innovative solutions grounded in generative AI. By combining theoretical frameworks with actionable insights, this book serves as a roadmap for organizations looking to fortify their defenses in an era of unprecedented cyber threats, making it an essential resource for anyone invested in the evolving landscape of cybersecurity and AI. Fortify your digital defenses with this essential book, which provides a roadmap for moving beyond the limitations of traditional encryption by leveraging generative AI algorithms to proactively anticipate, detect, and mitigate the next generation of cyber threats in real-time. In recent years, encryption has shown limitations as the sole safeguard against cyber threats in an increasingly interconnected world. While encryption remains a crucial component of cybersecurity, it is no longer sufficient to combat the evolving tactics of malicious actors. This book advocates for a paradigm shift towards leveraging generative AI algorithms to anticipate, detect, and mitigate emerging threats in real-time. Through detailed case studies and practical examples, the book illustrates how these AI-driven approaches can augment traditional security measures, providing organizations with a proactive defense against cyberattacks. It explores the connections between artificial intelligence and cybersecurity, exploring how generative AI technologies can revolutionize security paradigms beyond traditional encryption methods. Authored by leading experts in both AI and cybersecurity, the book presents a comprehensive examination of the challenges facing modern digital security and proposes innovative solutions grounded in generative AI. By combining theoretical frameworks with actionable insights, this book serves as a roadmap for organizations looking to fortify their defenses in an era of unprecedented cyber threats, making it an essential resource for anyone invested in the evolving landscape of cybersecurity and AI. Santosh Kumar Srivastava, PhD is an Associate Professor in the Department of Applied Computational Science and Engineering at the GL Bajaj Institute of Technology and Management with more than 21 years of experience. He has published more than 15 papers in reputed national and international journals and conferences and five patents. He is a distinguished researcher in the areas of computer networking, wireless technology, network security, and cloud computing. Durgesh Srivastava, PhD is an Associate Professor in the Chitkara University Institute of Engineering and Technology at Chitkara University with more than 14 years of academic and research experience. He has published more than 30 papers in reputed national and international journals and conferences, as well as several books and patents. His research interests include machine learning, soft computing, pattern recognition, and software engineering, modeling, and design. Manoj Kumar Mahto, PhD is an Assistant Professor at BRCM College of Engineering and Technology. Bahal, Haryana, India. He has published more than 15 journal articles, ten book chapters, and three patents. His research interests encompass AI and machine learning, image processing, and natural language processing. Ben Othman Soufiane, PhD works in the Programming and Information Center Research Laboratory associated with the Higher Institute of Informatics and Techniques of Communication. He has published more than 70 papers in reputed international journals, conferences, and book chapters. His research focuses on the Internet of Medical Things, wireless body sensor networks, wireless networks, artificial intelligence, machine learning, and big data. Praveen Kantha, PhD is an Associate Professor in the School of Engineering and Technology at Chitkara University. He is the author of 20 research papers published in national and international journals and conferences, several book chapters, and two patents. His research interests include machine learning, intrusion detection, big data analytics, and autonomous and connected vehicles.
Context-based Modeling of Activity in Real-World Projects
Context-based Modeling of Activity in Real-World Projects presents a synthesis of 25 years of research on modeling and using context in real-world applications in a very large spectrum of domains, which allows us to illustrate the keystone aspects of context from an initial operational definition; this opens up a four-level framework under conceptual, operational, implementation and environment aspects of activity modeling. The result is the Contextual-Graphs (CxG) formalism, thanks to strong connections between context and an actor’s focus of attention, leading to a uniform representation of knowledge, reasoning and context for actor and group activity. The results of this research constitute the building blocks for designing future types of AI systems, namely the context-based intelligent assistant systems. This book presents the proceduralized context as a new definition of context, that is a real-time definition, which is then applied to context modeling for actor or group activity – before finally elaborating the two versions of the CxG formalism including uses in different modeling. Patrick Brézillon works in artificial intelligence. His research includes a four-level scientific approach leading to contextual-graph formalism, a real-time definition of context. His objective is the design of context-based intelligent assistant systems.
Adversarial Machine Learning
Enables readers to understand the full lifecycle of adversarial machine learning (AML) and how AI models can be compromised Adversarial Machine Learning is a definitive guide to one of the most urgent challenges in artificial intelligence today: how to secure machine learning systems against adversarial threats. This book explores the full lifecycle of adversarial machine learning (AML), providing a structured, real-world understanding of how AI models can be compromised—and what can be done about it. The book walks readers through the different phases of the machine learning pipeline, showing how attacks emerge during training, deployment, and inference. It breaks down adversarial threats into clear categories based on attacker goals—whether to disrupt system availability, tamper with outputs, or leak private information. With clarity and technical rigor, it dissects the tools, knowledge, and access attackers need to exploit AI systems. In addition to diagnosing threats, the book provides a robust overview of defense strategies—from adversarial training and certified defenses to privacy-preserving machine learning and risk-aware system design. Each defense is discussed alongside its limitations, trade-offs, and real-world applicability. Readers will gain a comprehensive view of today?s most dangerous attack methods including: Evasion attacks that manipulate inputs to deceive AI predictions Poisoning attacks that corrupt training data or model updates Backdoor and trojan attacks that embed malicious triggersPrivacy attacks that reveal sensitive data through model interaction and prompt injectionGenerative AI attacks that exploit the new wave of large language models Blending technical depth with practical insight, Adversarial Machine Learning equips developers, security engineers, and AI decision-makers with the knowledge they need to understand the adversarial landscape and defend their systems with confidence. Enables readers to understand the full lifecycle of adversarial machine learning (AML) and how AI models can be compromised Adversarial Machine Learning is a definitive guide to one of the most urgent challenges in artificial intelligence today: how to secure machine learning systems against adversarial threats. This book explores the full lifecycle of adversarial machine learning (AML), providing a structured, real-world understanding of how AI models can be compromised—and what can be done about it. The book walks readers through the different phases of the machine learning pipeline, showing how attacks emerge during training, deployment, and inference. It breaks down adversarial threats into clear categories based on attacker goals—whether to disrupt system availability, tamper with outputs, or leak private information. With clarity and technical rigor, it dissects the tools, knowledge, and access attackers need to exploit AI systems. In addition to diagnosing threats, the book provides a robust overview of defense strategies—from adversarial training and certified defenses to privacy-preserving machine learning and risk-aware system design. Each defense is discussed alongside its limitations, trade-offs, and real-world applicability. Readers will gain a comprehensive view of today???s most dangerous attack methods including: Evasion attacks that manipulate inputs to deceive AI predictions Poisoning attacks that corrupt training data or model updates Backdoor and trojan attacks that embed malicious triggersPrivacy attacks that reveal sensitive data through model interaction and prompt injectionGenerative AI attacks that exploit the new wave of large language models Blending technical depth with practical insight, Adversarial Machine Learning equips developers, security engineers, and AI decision-makers with the knowledge they need to understand the adversarial landscape and defend their systems with confidence. Jason Edwards, DM, CISSP, is an accomplished cybersecurity leader with extensive experience in the technology, finance, insurance, and energy sectors. Holding a Doctorate in Management, Information Systems, and Technology, Jason specializes in guiding large public and private companies through complex cybersecurity challenges. His career includes leadership roles across the military, insurance, finance, energy, and technology industries. He is a husband, father, former military cyber officer, adjunct professor, avid reader, dog dad, and popular on LinkedIn.
Practical Playwright Test
Gain cutting-edge skills in crafting reliable, efficient end-to-end tests with Playwright Test. This book is your comprehensive guide to Playwright Test that will help you to create and debug blazing fast tests, and integrate and customize Playwright Test to fit your testing needs. The book begins with an introduction to Playwright and teaches you the fundamentals of how to write tests efficiently. The book then gets into concepts like Locators and explains how to set up a CI using Playwright Test. After this, you will gain experience in two important aspects of testing – speed and customization. You will then be taken through a deep dive into Fixtures followed by an exploration of strategies like mocking and emulation through which you can achieve more control of the testing environment. The book also provides a detailed discussion on flakiness and how Playwright Test can help you with it. It then teaches you how to automate tests and ends with a discussion on how Playwright Test changes the landscape of testing, and how to integrate it in your daily practices and testing strategy. By reading this book, you will become an expert in the specificities of Playwright Test and how to test critical user flows, reduce bugs in production, and ultimately ship reliable software with confidence. What You Will Learn Create and debug reliable end-to-end tests efficiently with the perfect locatorsSet up a CI using Playwright Test to get results, test reports and useful tracesUnderstand how to use and write FixturesCustomize Playwright to fit your needs Who This Book Is For Frontend developers, full-stack developers, QA Engineers, Software Testers, Test Automation Engineers, QA Leads and QA Managers
The LearnEdge(TM) Perspective
Decision Intelligence integrates five elements: 1. Facts under your control. 2. Facts outside of your control. 3. Outcomes expected. 4. Transformation engine. 5. A feedback loop. The essence of success.
Introduction to Programming for Researchers
Enhance your computational and programming skills using Bash and Python to improve productivity and efficiency in research projects. This book is an essential guide for STEM researchers. Structured into several parts, each builds on the previous ones to ensure a solid foundation in programming. You’ll begin with the basics of digital computation and operating systems, then write pipelines and scripts in Bash, focusing on tools for working with datasets in text files. After introducing algorithms and floating-point numbers, the book transitions to Python, emphasizing SciPy libraries and built-in features like type hints and f-strings. IPython and Jupyter notebooks are integrated into the lessons throughout. Programming best practices are taught, alongside programming basics. These include documentation and unit testing. As the target audience is STEM students and professionals, examples make heavy use of datasets and the SciPy software stack, especially NumPy, Matplotlib, Pandas, and SymPy. Introduction to Programming for Researchers will foster a deeper understanding of computational tools and critical programming skills, empowering you to tackle complex datasets and enhance their research capabilities. What You Will Learn Apply programming skills to enhance research productivity and efficiency.Write Bash pipelines and executable scripts.Implement basic algorithms in Python, focusing on time efficiency and structured programming. Who This Book Is For Experienced researchers looking to improve their computational skills; students in the natural sciences and engineering; scientists and engineers from various fields, seeking to integrate programming skills into their research methodologies.
GameMaker Programming Challenges
Upgrade your GameMaker programming skills with 500 programming challenges. The book is a collection of programming challenges, covering a range from simple to advanced concepts. GameMaker is a hugely popular tool and is regarded one of the best approaches for 2D games. GameMaker allows both visual and code-based approach for game development and has been used for multiple hit titles. Each chapter covers a certain programming element, such as Sprite Fonts, Projectiles, Mechanics, etc. The book is designed in a manner where each challenge provides an outline of the problems, useful functions, hints on tackling the challenge, and an example solution. On completion, you will take away new knowledge of GameMaker functions, an ability to think logically when developing code, and a better understanding of game design and planning. What You Will Learn Study the new GML, from basic functions to more evolved concepts.Gain ability to view example solutions when necessary.Increase your understanding of game design concepts. Who Is This Book For Beginners to intermediate level readers with basic understanding of GameMaker’s IDE, including creating object, sprite, and sound assets will benefit from this book.
Regenerative Zukünfte und künstliche Intelligenz
Dieses Buchprojekt erscheint in drei Teilen mit jeweils einem inhaltlichen Schwerpunkt – PLANET, PEOPLE, PROFIT – und beschäftigt sich übergreifend mit den Nachhaltigkeitszielen der Vereinten Nationen (Sustainable Development Goals, SDGs). Dieser dritte Band behandelt die ökonomische Dimension der Nachhaltigkeit und umfasst Beiträge, die explizit oder implizit SDGs mit Wirtschaftsbezug thematisieren. Die Beiträge und Grußworte international renommierter Expert:innen aus Wissenschaft und Praxis werden durch Begleittexte der Herausgebenden ergänzt. „KI hilft uns dabei, die Natur besser zu verstehen und die Maßnahmen zu ihrem Schutz und ihre Wiederherstellung auf ein stabiles Fundament zu stellen. Das wird nicht nur helfen, unsere Lebensgrundlage zu sichern, sondern auch zur Entwicklung neuer Geschäfts- und Finanzierungsmodelle beitragen“, aus dem Grußwort von Dr. Frauke Fischer.
AI in Legal Tech
Explore the risks, opportunities, and practicalities of generative AI in legal practice In AI in Legal Tech: How Generative AI Is Transforming Legal Technology and the Practice of Law, legal-tech pioneer and guru, Catherine Casey, walks you through the risks and opportunities presented by generative AI in the legal industry. She offers a comprehensive and accessible discussion of generative AI’s immediate and near-future impact on legal practices, ethics, and careers in law. The book translates and simplifies the complexities of generative AI and presents practical advice for anyone interested in harnessing its potential to dramatically redefine legal practice. It balances engaging narrative with expert analysis and is tailored specifically for non-technical legal professionals doing their best to navigate a new—and rapidly evolving—technological frontier. The author has also included a “Prompt Primer: Lawyered Edition” for practicing lawyers. Perfect for practicing lawyers, law students, legal technologists, and law practice managers, AI in Legal Tech is also a must-read resource for everyone who finds themselves at the intersection of law and technology. Explore the potential and risks of generative AI in the legal industry In AI in Legal Tech: How Generative AI Is Transforming Legal Technology and the Practice of Law, legal-tech pioneer and guru Catherine Casey—aka, TechnoCat—delivers a startlingly insightful and up-to-date discussion of the risks and opportunities presented by generative AI in the legal sector. The author walks you through generative AI's impact on the practice of law, legal ethics, and legal careers, offering guidance and clarity on a rapidly evolving technology. Balancing engaging narrative with expert analysis, AI in Legal Tech is written specifically for non-technical legal professionals and students doing their best to navigate the intersection of technology and law. You'll find: Explanations of how AI is shaping new legal careers and what you can do to find success in your ownA “Legal Tech Survival Kit,” complete with a comprehensive Legal AI glossary and must-try tools for tech-savvy lawyersInsights from the “front lines” of legal AI and the people designing the technologies shaping tomorrow's legal industry Perfect for practicing lawyers, law students, and law practice managers, AI in Legal Tech will also prove invaluable to legal technologists, paralegals, and anyone else interested in the application of the latest tech to the legal field. CAT CASEY is the defining voice at the intersection of AI and legal technology. A twenty-year veteran of the field and CEO of The Technocat LLC, she’s led technology and innovation at multiple legal tech Unicorns, the Big Four, and AmLaw 10 firms. Known for her sharp insight, deep technical fluency, and signature irreverence, Cat has helped shape how the legal profession navigates the age of intelligent machines.
AI in Business For Dummies
Unlock productivity and profit with AI AI is suddenly a must-have in today’s business world. AI in Business For Dummies shows you what AI can do for your organization. This practical, jargon-free guide explains how AI works and how you can use it to boost your competitive edge. With step-by-step guidance, you’ll learn to harness AI wins—better decision-making, quicker content generation, more personalized customer interactions, and beyond—without sacrificing the human element. Get on the AI train and future-proof your business with this easy-to-use Dummies guide. Inside… Grasping AI basicsWinning customers with AISpeeding up innovationGetting your team on boardStaying legal and ethicalAvoiding common pitfallsPreparing for the next wave of new AI technologies Create an AI strategy that best fits your business You've heard about how artificial intelligence will revolutionize business, but maybe you're not sure how it will revolutionize your business. In AI in Business For Dummies, AI researcher and consultant Jeffrey Allan delivers clear insight into the capabilities of AI, the AI tools that get the job done, and how to best put artificial intelligence to work in your company. Using the book's step-by-step instructions, you'll learn how to build the latest AI tech in your business strategies. You'll also discover real-world examples of effective AI implementations in tasks like workflow automation, closing sales, handling data analytics, and driving innovation. The book also dives into ideas on how to get your staff and colleagues on board as well as how to use AI in an ethical manner. AI in Business For Dummies also includes: A breakdown of the essentials of AI technology and how each intersects with business useWays to avoid common business AI mistakes and pitfallsTips on future-proofing your AI investment Perfect for managers, executives, entrepreneurs, founders, and other business leaders, AI in Business For Dummies is a must-read resource for anyone with an interest in taking advantage of the newest, most exciting technologies in business. Dr. Jeffrey Allan directs the Institute for Responsible Technology and Artificial Intelligence at Nazareth University, developing AI-focused degree programs. An expert in AI and psychology, he’s advised Fortune 500 firms and Silicon Valley startups, and he coauthored Writing AI Prompts For Dummies.
AI ChatBots For Dummies
Easy and effective strategies for using AI chatbots Turn your business into a 24/7 customer service powerhouse with AI chatbots that work around the clock! Perfect for anyone drowning in customer emails or missing sales opportunities while they sleep, AI Chatbots For Dummies explains how to build intelligent chatbots from scratch — no coding required. You’ll discover how major companies use chatbots to boost efficiency and customer satisfaction and learn to create your own automated assistants for customer service, lead generation, and marketing campaigns that practically run themselves. Inside …Build no-code solutionsCreate 24/7 customer supportAccelerate lead generationConvert leads into customersReduce overhead and workloadImprove customer satisfactionScale your companyIntegrate the newest tools A handbook for professionals implementing or upgrading chatbots In AI Chatbots For Dummies, chatbot expert Kelly Mirabella and veteran tech educator Eric Butow deliver a from-scratch guide to deploying AI-powered chatbots that keep your business' customers happy. The book offers step-by-step instructions to building your bot and putting it into use — even if you don't know how to code. You'll learn how to reduce your workload, improve your company's efficiency, increase customer satisfaction, and accomplish a ton of other useful business goals, like creating automated marketing campaigns and new sales strategies. The authors walk you through exactly how you can use chatbots in a variety of use cases, from generating leads and sales to gathering audience and customer data and growing an audience. You'll also learn how to: Automate customer service and support, ensuring your customers remain loyal and satisfiedMeasure the success of your chatbots and expand their capabilities over timeConnect your chatbots to other systems and tools, including email, CRMs, calendars, and more AI Chatbots For Dummies is the perfect how-to guide for business owners, entrepreneurs, and other business leaders interested in using chatbots to upgrade their company's abilities, improve its efficiency, and grow its bottom line. Kelly Noble Mirabella is a chatbot expert specializing in AI-powered customer engagement solutions. Eric Butow is a 54x business and technology author who has co-authored multiple For Dummies titles including Instagram For Business For Dummies and Digital Etiquette For Dummies.
Scrum - verstehen und erfolgreich einsetzen (4. Auflg.)
Das ultimative Scrum-Handbuch Didaktisch sehr gut aufgebautes Grundlagenbuch Mit Empfehlungen der Autoren aus der Praxis für die Praxis Geeignet auch für Scrum-Zertifizierungskurse: Scrum Basics, Certified Scrum Master Scrum dient dem agilen Management innovativer Produktentwicklung mit selbstorganisierten Teams. Mit seinem iterativ-inkrementellen Ansatz führt Scrum zu mehr Transparenz und Flexibilität als klassische sequenzielle Entwicklungsmethoden. Die Autoren beschreiben in kompakter Form die Scrum-Grundlagen sowie die hinter Scrum stehenden Werte und Prinzipien. Dabei unterscheiden sie zwischen produktbezogenen Aspekten, entwicklungsbezogenen Aspekten und dem kontinuierlichen Verbesserungsprozess. Im Einzelnen werden behandelt: Scrum-Historie sowie Vorteile und Eignung von Scrum Scrum-Flow und die Verantwortlichkeiten in Scrum (Product Owner, Entwickler:innen, Scrum Master, Scrum-Team) Scrum-Meetings: Sprint Planning, Daily Scrum, Sprint Review, Sprint Retrospektive Artefakte: Product Backlog, Sprint Backlog, lieferbares Produktinkrement Releasemanagement und Schätzverfahren Einführung von Scrum im Unternehmen, Scrum-Skalierung und verteiltes Scrum Vertragsgestaltung für agile Entwicklung und Leadership Im Anhang werden die Elemente des Scrum-Frameworks sowie einige häufig anzutreffende Praktiken noch einmal in Kurzform dargestellt. Die 4. Auflage wurde mit weiteren Praxistipps ergänzt und in vielen einzelnen Aspekten erweitert.
Standardising Carbon Markets
Carbon markets are expected to grow from 10-20 billion USD per year to more than 200 billion USD by 2035. How can you take part in this ecosystem? How can your business benefit by incorporating blockchain solutions in a broader way? This book will explore solutions that utilize blockchain technology and tokenization to deliver efficient, transparent, trustworthy and interoperable carbon offsetting solutions for small and medium-sized businesses and consumers. Software and hardware developers will be provided with an introduction to key players in the carbon offsetting universe and associated markets and industries globally. Readers will learn how to: · Outline how the technology that supports carbon markets is driving genuine climate change · Describe the complexity and different players in the carbon offsetting ecosystem including developers of carbon-offsetting projects, infrastructure providers, buyers, and financiers · Describe blockchain technology and its benefits to carbon markets – transparency, traceability, accountability · Provide a complex discussion on regulatory initiatives and standards that drive positive change in carbon markets, beginning with those that apply to the physical domain (e.g., energy, agriculture), how data is collected, processed, validated and verified right up to financing/trading projects · Analyze how blockchain will help your carbon offsets business · Apply Web 3 technology to overcome data quality challenges in carbon markets Target audience This book is for project developers (those involved in reducing green house gas emissions), computer software developers working in Web 2 or Web 3 environments, others in the tech community, educated professionals, business managers and owners who are interested in buying or selling carbon credits, NGOs and Non-profits, Academic Institutions.
Hyper-Intelligent Networks
Prepare for the next technological frontier with this essential, multidisciplinary guide that delves into hyper-intelligent networks, providing a comprehensive overview of how AI and machine learning are revolutionizing telecommunications, healthcare, and other vital sectors with cognitive, autonomous connectivity. As we stand on the brink of a new technological frontier, the convergence of artificial intelligence, machine learning, and network infrastructure promises to revolutionize the way we harness the power of digital ecosystems. The vision of a hyper-intelligent network transcends conventional notions of connectivity and represents a paradigm shift where networks evolve from mere conduits of data to dynamic entities with cognitive capabilities, adaptability, and autonomous decision-making abilities. This book delves into the emerging field of hyper-intelligent networks, exploring how these networks are poised to revolutionize various sectors, including telecommunications, healthcare, finance, and transportation. It provides a comprehensive overview of the theoretical foundations, practical applications, and future implications of hyper-intelligent networks, offering a deeper understanding of this cutting-edge technology. Written by leading experts in the fields of artificial intelligence and networking, the book has a multidisciplinary approach that combines theoretical insights with real-world case studies and practical examples. It is suitable for both technical professionals seeking to deepen their understanding of hyper-intelligent networks and non-technical readers interested in the potential impact of these technologies on society. Readers will find the book: Discusses different applications of hyper-intelligent networks in various industries;Introduces the innovative potential of hyper-intelligent networks;Presents state-of-the-art analyses and real-world case studies demonstrating hyper-intelligent networks;Provides a comprehensive look at applications of hyper-intelligent networks across a number of industries. Audience Research scholars, IT professionals, network administrators, cybersecurity experts, government research agencies, and engineering students. Pradosh Kumar Gantayat, PhD is an Assistant Professor at the Department of Artificial Intelligence and Data Science, Faculty of Science and Technology (IcfaiTech), ICFAI Foundation for Higher Education (IFHE), Deemed to be University, Hyderabad, Telangana, India. He has published more than 25 papers in international journals, conferences, and book chapters and holds three Indian patents. His research focuses on security issues in computer networks, soft computing, AI, and optimization algorithms. Sandeep Kumar Panda, PhD is a Professor Department of Artificial Intelligence and Data Science, Faculty of Science and Technology (IcfaiTech), ICFAI Foundation for Higher Education (IFHE), Deemed to be University, Hyderabad, Telangana, India. He has published more than 70 articles in and international journals and conferences and edited six books. His research interests include blockchain technology, W3, Metaverse, the Internet of Things, AI, and cloud computing. S. Balamurugan, PhD is the Director of Research and Development at Intelligent Research Consultancy Services. He has published 48 books, more than 300 articles in international journals and conferences, and 55 patents. His research interests include artificial intelligence, augmented reality, Internet of Things, big data, and cloud and wearable Computing. Sheng-Lung Peng, PhD is a Professor and the Director of the Department of Creative Technologies and Product Design at the National Taipei University of Business, Taiwan. He has edited several special issues of journals and published more than 100 research papers. His research interests focus on designing and analyzing algorithms for bioinformatics, combinatorics, data mining, and other network areas.
Behind the AI Mask
A hands-on guide to mitigating the risks posed by deepfake technologies In Behind the AI Mask: Protecting Your Business from Deepfakes, experienced technologist and founder of the viral platform, Myster Giraffe, Carl Bogan, walks you through the risks and benefits presented by deepfake technologies. He explains how to stay ahead of the curve on this rapidly evolving tech, showing you how to manage and mitigate the harms caused by maliciously deployed deepfakes. The book demonstrates how deepfake technology has changed recently, the current state of the phenomenon, and the practical steps you can take now to detect deepfakes in real time and catch scammers in the act. You’ll discover early detection strategies that can prevent attacks before they start, as well as simple techniques that permit you to embrace AI technology without experiencing the pitfalls associated with it. Behind the AI Mask is a must-read for managers, executives, and other business leaders who are ready to set up effective defenses against the reputational and financial harms caused by deepfakes. It’s packed with tangible, practical strategies you can implement immediately in any industry. A practical, hands-on guide to navigating deepfake technology and reducing the risks it poses to your business In Behind the AI Mask: Protecting Your Business From Deepfakes, technologist and founder of viral platform, Myster Giraffe, Carl Bogan, explains the dangers, benefits, and potential of deepfake technology. He walks you through how to stay ahead of the risks that businesses face from maliciously deployed deepfake technology, showing you exactly how the tech has evolved and the practical steps you need to take to detect deepfakes in real time and catch scammers in the act. You'll find practical strategies that will save your company time and money and protect against long-lasting reputational harms. You'll also discover early detection strategies that stop incidents before they even begin. Inside the book: The future of artificial intelligence and deepfake tech — learn what's coming next in AI innovationTechniques for embracing AI technology without running afoul of the pitfalls that come along with itStraightforward and accurate explainers of what exactly deepfakes are, how they're used (both legitimately and maliciously), and how they can harm your company An essential and timely resource for managers, executives, and business leaders, Behind the AI Mask is a must-read for everyone worried about the reputational and financial risks posed by deepfakes and those looking for tangible, practical ways to mitigate those risks. CARL BOGAN pioneered viral deepfake technology as creator of Myster Giraffe, generating hundreds of millions of views across social media. With over 20 years in visual effects for Disney, Paramount, Apple, Google, and Sony, he brings a unique perspective to deepfake defense—understanding how these illusions are crafted from the artist’s side, not the IT department. He has taught workshops internationally, including at Cisco, helping organizations see deepfake threats through the eyes of the creators who build them.
AI in Business For Dummies
Unlock productivity and profit with AI AI is suddenly a must-have in today’s business world. AI in Business For Dummies shows you what AI can do for your organization. This practical, jargon-free guide explains how AI works and how you can use it to boost your competitive edge. With step-by-step guidance, you’ll learn to harness AI wins—better decision-making, quicker content generation, more personalized customer interactions, and beyond—without sacrificing the human element. Get on the AI train and future-proof your business with this easy-to-use Dummies guide. Inside… Grasping AI basicsWinning customers with AISpeeding up innovationGetting your team on boardStaying legal and ethicalAvoiding common pitfallsPreparing for the next wave of new AI technologies Create an AI strategy that best fits your business You've heard about how artificial intelligence will revolutionize business, but maybe you're not sure how it will revolutionize your business. In AI in Business For Dummies, AI researcher and consultant Jeffrey Allan delivers clear insight into the capabilities of AI, the AI tools that get the job done, and how to best put artificial intelligence to work in your company. Using the book's step-by-step instructions, you'll learn how to build the latest AI tech in your business strategies. You'll also discover real-world examples of effective AI implementations in tasks like workflow automation, closing sales, handling data analytics, and driving innovation. The book also dives into ideas on how to get your staff and colleagues on board as well as how to use AI in an ethical manner. AI in Business For Dummies also includes: A breakdown of the essentials of AI technology and how each intersects with business useWays to avoid common business AI mistakes and pitfallsTips on future-proofing your AI investment Perfect for managers, executives, entrepreneurs, founders, and other business leaders, AI in Business For Dummies is a must-read resource for anyone with an interest in taking advantage of the newest, most exciting technologies in business. Dr. Jeffrey Allan directs the Institute for Responsible Technology and Artificial Intelligence at Nazareth University, developing AI-focused degree programs. An expert in AI and psychology, he’s advised Fortune 500 firms and Silicon Valley startups, and he coauthored Writing AI Prompts For Dummies.
Agentic AI For Dummies
Implement autonomous AI that thinks for itself Ready to discover AI that doesn’t just respond but thinks, plans, and acts independently? Agentic AI represents the next evolutionary leap in artificial intelligence – systems that plan their own path, make strategic decisions, learn as they go, and solve complex problems without constant human guidance. This book shows you how agentic systems work, where they’re effective, and how they’ll transform your business and daily life. From autonomous healthcare diagnostics to self-managing business operations, you’ll explore the exciting possibilities that come with truly autonomous AI. Inside… Separate Agentic AI hype from realityExplore underlying architecture, models, and protocolsDiscover Agentic AI use casesOptimize your business operationsNavigate ethical and governance issuesDesign agentic systems responsiblyUpgrade your AI-engagement skillsPrepare for changes to your business An easy-to-follow guide to demystifying Agentic AI, the next step in the evolution of artificial intelligence Agentic AI is the next big leap in artificial intelligence. Agentic systems don't just respond to commands. They set goals, make decisions, and take initiative without direct human interaction. Sound like a lot to wrap your head around? Fortunately Agentic AI For Dummies is here to help you gain understanding of this advancing technology. Written by the author of ChatGPT For Dummies and Generative AI For Dummies, this easy-to-understand tech guide helps you take your first steps into Agentic AI. Get insight into the technologies driving Agentic AI, a road map for shifting from legacy systems to Agentic systems, and a tour of real-world use cases for Agentic AI. This books arms you with an understanding to make better decisions about how and when to use Agentic AI technologies. Inside the book: Discussions of the technological foundations of agentic AIExplorations of the wide variety of applications of the AI agents, including in scientific research, innovation, business operations, healthcare, and moreInsightful examinations of the ethical considerations and hurdles you'll need to navigate when it's time to deploy agentic AI in your company Perfect for business owners, entrepreneurs, managers, executives, professionals and team leaders in the private sector, Agentic AI For Dummies is a hands-on toolkit and strategy guide for using autonomous AI solutions to solve hard problems in your organization. Pam Baker has nearly two decades of experience as a tech journalist, consultant, and trainer. She’s the author of ChatGPT For Dummies and Generative AI For Dummies. Based in metro Atlanta, she helps readers navigate emerging technologies with clarity and practical insights.
Lessons from the Frontlines
“Reading this book feels like sitting down with a trusted mentor who has lived through every security challenge you can imagine. Assaf writes with the simplicity and authenticity of someone who’s been in the trenches, made hard calls, and learned from both wins and setbacks.” —ROSS HALELIUK, Security Industry Expert “Building and sustaining security in major enterprises is much more than a technical discipline. Rather, it’s an intense leadership challenge balancing influence, grit and team building. Assaf’s personal journey revealed in this book contains lessons for all security professionals—whether you are starting out or an established leader you will love this.” —PHIL VENABLES, Former CISO at Goldman Sachs and Google Cloud, and a VC Partner Master the human skills that effective cybersecurity leaders need with actionable advice from a 25+ year veteran of the industry In Lessons from the Frontlines: Insights from a Cybersecurity Career, Chief Security Officer at Qualtrics, Assaf Keren, draws on over 25 years’ experience in cybersecurity to offer clear, actionable guidance for leading cybersecurity teams. Keren tackles the most pressing problems security leaders face, including execution under pressure, burnout, organizational resistance, and the gap between technical rigor and business reality. He shows you how to address these challenges by replacing permission-seeking with intent-based action, communicating risk with realistic hope, and building teams that thrive amid nonstop change. The book develops personal foundations (curiosity, grit, optimism), core leadership competencies (execution, change management, business and finance acumen, diplomacy, and communication), the human side of leadership (mental health, self- care, community), and strategic scale (leading diverse organizations, product thinking in security). Real-world stories—from incident command to rebuilding global security operations, and a case study on generative AI adoption—pair with frameworks you can apply immediately. Perfect for current and aspiring CISOs, security directors, and team leads, Lessons from the Frontlines is also a must-read for all technical and business professionals interested in achieving or understanding cybersecurity leadership roles. Transform your approach to cybersecurity leadership with specific, actionable techniques from a 25+ year veteran of the industry In Lessons from the Frontlines: Insights from a Cybersecurity Career, a 25+ year veteran of cybersecurity leadership, Assaf Keren, delivers an essential new approach to leading cybersecurity teams. Keren combines engaging, real-life stories drawn from decades spent in the industry – including his current role as Chief Security Officer at Qualtrics and former Chief Information Security Officer in PayPal – with hands-on, specific frameworks for implementing effective solutions in an environment that doesn’t tolerate error. Lessons from the Frontlines goes beyond generic theory and high-level concepts. It dives deep into practical strategies for working cybersecurity professionals, explaining how to develop the personal characteristics you’ll need to succeed, build leadership competencies your teams will expect from you, address your own mental and physical health needs so you can deal with the challenges you’ll face, and apply all these lessons at scale in organizations of any size. The author walks you through: How to move from permission-seeking approaches to intent-based action that allows you to execute solutions in dynamic environments in real timeStrategies for maintaining optimism and a healthy outlook that permits you to endure difficult periods and excel in adversityTechniques for building proactive, forward-thinking, and creative solutions that achieve more than reactive and defensive responses to threats Perfect for practicing and aspiring cybersecurity executives, Lessons from the Frontlines is a must-read strategy guide for all cybersecurity practitioners and professionals interested in rising to – or excelling in – cybersecurity leadership roles. ASSAF KEREN is the Chief Security Officer at Qualtrics and the former Chief Information Security Officer at PayPal. He has more than 25 years’ experience working in the cybersecurity industry as a practitioner and leader and has been involved in military intelligence, startups, Fortune 500 companies, and boards of directors.
The Practical Guide to Large Language Models
This book is a practical guide to harnessing Hugging Face's powerful transformers library, unlocking access to the largest open-source LLMs. By simplifying complex NLP concepts and emphasizing practical application, it empowers data scientists, machine learning engineers, and NLP practitioners to build robust solutions without delving into theoretical complexities. The book is structured into three parts to facilitate a step-by-step learning journey. Part One covers building production-ready LLM solutions introduces the Hugging Face library and equips readers to solve most of the common NLP challenges without requiring deep knowledge of transformer internals. Part Two focuses on empowering LLMs with RAG and intelligent agents exploring Retrieval-Augmented Generation (RAG) models, demonstrating how to enhance answer quality and develop intelligent agents. Part Three covers LLM advances focusing on expert topics such as model training, principles of transformer architecture and other cutting-edge techniques related to the practical application of language models. Each chapter includes practical examples, code snippets, and hands-on projects to ensure applicability to real-world scenarios. This book bridges the gap between theory and practice, providing professionals with the tools and insights to develop practical and efficient LLM solutions. What you will learn: What are the different types of tasks modern LLMs can solveHow to select the most suitable pre-trained LLM for specific tasksHow to enrich LLM with a custom knowledge base and build intelligent systemsWhat are the core principles of Language Models, and how to tune themHow to build robust LLM-based AI Applications Who this book is for: Data scientists, machine learning engineers, and NLP specialists with basic Python skills, introductory PyTorch knowledge, and a primary understanding of deep learning concepts, ready to start applying Large Language Models in practice.
Generative KI-Systeme entwickeln
Von der Idee zur KI-Anwendung – praxisnah und fundiert Ein Leitfaden für alle wesentlichen Aspekte der Entwicklung generativer KI-Systeme, inklusive Prompt Engineering, RAG, Finetuning und Agenten Das Buch bietet ein Framework für den Einsatz von KI in realen Anwendungen Es deckt den kompletten Entwicklungszyklus von KI-Systemen ab, von der Modellentwicklung bis zum produktiven Betrieb In diesem Praxishandbuch beschreibt Bestsellerautorin Chip Huyen die Werkzeuge des KI-Engineerings und den Prozess der Erstellung von KI-Anwendungen mithilfe generativer Foundation Models. Das Buch deckt den kompletten Entwicklungszyklus von KI-Systemen ab, von der Modellentwicklung bis zum produktiven Betrieb. Entwickler und Entwicklerinnen von KI-Anwendungen erfahren, wie sie sich in der KI-Landschaft zurechtfinden – bei Modellen, Datensätzen, Bewertungs-Benchmarks und der scheinbar unendlichen Zahl von möglichen Anwendungsmustern. Das Buch bietet damit einen praxisorientierten Rahmen für die Entwicklung produktionsreifer generativer KI-Systeme – mit klarem Fokus auf aktuellen Tools, Herausforderungen und Potenzialen im KI-Engineering. Erfahren Sie, was KI-Engineering ist und wie es sich vom traditionellen Machine-Learning-Engineering unterscheidet Machen Sie sich mit dem Prozess der KI-Anwendungsentwicklung vertraut und lernen Sie die typischen Herausforderungen sowie mögliche Lösungsansätze kennen Erkunden Sie verschiedene Techniken zur Modellanpassung wie Prompt Engineering, RAG, Finetuning, Agenten und Dataset Engineering und verstehen Sie deren Funktionsweise Untersuchen Sie die Engpässe hinsichtlich Latenz und Kosten bei der Bereitstellung von Foundation Models und lernen Sie, wie Sie diese überwinden können Wählen Sie das passende Modell und die richtigen Metriken, Daten und Entwicklungsmuster für Ihre Anforderungen aus
Prompting kurz & gut
Kompakte und intelligente Einführung ins Prompting und in LLMs Verstehen, wie Large Language Models »denken« und sprechen Mit Best Practices und grundlegenden Strategien effektiv prompten Mit fortgeschrittenen Prompting-Techniken wie Systemprompts, benutzerdefinierten GPTs und Meta-Prompting zum Profi werden Mit externen Tools Prompts schneller schreiben und besser verwalten Praxis-Beispiele aus der IT: vom Codieren über Architekturüberlegungen bis zur automatisierten Dokumentation Prompting – klingt einfach, hat es aber in sich. Wer Large Language Models wie ChatGPT, Claude oder Gemini treffsicher und effizient einsetzen will, braucht mehr als nur gute Fragen. Dieses kompakte Buch erklärt, wie Sprachmodelle »denken«, wie Prompts aufgebaut sein sollten – und wie sich mit Strategie, praktischem Know-how und den passenden Tools deutlich bessere Ergebnisse erzielen lassen. Ob Sie neu einsteigen oder Ihr Prompting verbessern möchten: Hier finden Sie fundiertes Wissen, klare Anleitungen und zahlreiche Praxistipps. Verstehen, wie Sprachmodelle funktionieren und wie man mit ihnen kommuniziert Best Practices für wirksame Prompts – praxisnah, präzise und auf den Anwendungsfall zugeschnitten Tools, Workflows und Chatbot-Features für produktiveres Arbeiten Praxisbeispiele aus der IT: von Code über Dokumentation bis Architektur Fortgeschrittene Techniken: Systemprompts, benutzerdefinierte GPTs, Meta-Prompting Rechtliches: Datenschutz, Urheber- und Nutzungsrechte im Blick behalten Mit umfangreichen Cheatsheets
Artificial Intelligence and IoT in Online Education Systems
Design the future of digital education with this essential book that provides a comprehensive guide to leveraging AI and IoT to create dynamic, inclusive virtual learning environments and effectively implement advanced online proctoring solutions. The rapid development of online learning environments and virtual classrooms, coupled with the need for scalable, personalized education systems, has positioned AI as a key enabler of modern education. The advent of these technologies promises to reshape how we deliver, monitor, assess, and evaluate online learning. This book explores these critical intersections of technology and education, emphasizing the potential of AI and IoT not only to optimize outcomes but also to create more dynamic, responsive, and inclusive virtual learning environments. Focusing on problems that can be solved through computer vision, video and audio streaming, class imbalance data, audio-to-text processes, multi-modal and bi-modal aspects, hand-written strokes, text similarity, biomedical ethics, and advancements in machine and deep learning algorithms, this book comprehensively explores the effectiveness of these technologies in online proctoring. This essential guide will equip educators, technologists, administrators, and policymakers with the knowledge and perspective necessary to leverage these technologies effectively. Readers will find the book: Explores various AI tools and techniques adopted for online proctoring examination systems;Covers critical analytical aspects of AI-assisted systems;Describes a variety of experiments leading to uni- and multi-modal systems and IoT-based architecture using computer vision, machine learning, and deep learning algorithms;Discusses the quality assurance and psychological aspects to preserve ethics during examinations. Audience Educational researchers and policymakers, as well as computer scientists working in AI, machine learning, data science, deep learning, computer vision, and statistics. Ramanujam E., PhD is an Assistant Professor in the Department of Computer Science and Engineering at the National Institute of Technology Silchar, Assam, India. He has contributed significantly to human activity recognition, especially online education and examinations, spam detection, and feature engineering across various domains. His areas of expertise include artificial intelligence, machine learning, deep learning, and ambient intelligence. Chandan Chakraborty, PhD is a Professor in the Department of Computer Science and Engineering at the National Institute of Technical Teachers’ Training and Research, Kolkata, West Bengal, India. He has more than 100 peer-reviewed publications in top journals and holds several patents. He specializes in artificial intelligence, machine learning, deep learning, and biomedical engineering.