Allgemein
Green Computational Intelligence
Transform your approach to technology and sustainability with this comprehensive guide to green computing and computational intelligence. The global pursuit of sustainability has placed an urgent emphasis on developing innovative and eco-friendly technological solutions. Green computing has the potential to revolutionize the way we evaluate sustainability with the use of energy-efficient algorithms for resource optimization, sustainable hardware design, and smart resource management. Recognizing the intersection of computational intelligence and environmental stewardship, this book seeks to address the pressing challenges of integrating green practices into the realm of computational intelligence and aligning them with global sustainable development goals. Through global expertise from researchers and industry professionals, this book comprehensively covers the many applications of these innovative new technologies, as well as the challenges surrounding their implementation. Readers will find the book: Explores the convergence of environmental sustainability and advanced computational techniques, addressing the global call for energy-efficient and eco-friendly technological solutions;Integrates perspectives from computer science, engineering, environmental science, and artificial intelligence, providing a holistic view of green computing;Examines sustainable practices across diverse topics, including energy-efficient algorithms and resource optimization, sustainable hardware design, green software engineering, eco-friendly data centers, and smart resource management;Offers practical strategies for implementing sustainable computing practices while addressing theoretical and practical challenges;Highlights the role of computational intelligence in promoting sustainability, bridging the gap between technology development and environmental conservation. Audience Researchers, students, educators, and industry professionals working towards sustainable practices in and using green technology. Nitish Pathak, PhD is an associate professor in the Department of Computer Science and Engineering, the Bhagwan Parshuram Institute of Technology, Guru Gobind Singh Indraprastha University, New Delhi, India with over 19 years of teaching experience. He has authored and edited over ten books and published over 125 articles in international journals, conferences, patents, and book chapters. His research interests include intelligent computing techniques, empirical software engineering, trusted operating systems, cloud computing, the IoT, and artificial intelligence. Neelam Sharma, PhD is a senior assistant professor in the Maharaja Agrasen Institute of Technology, Guru Gobind Singh Indraprastha University, New Delhi, India with over 19 years of teaching experience. She has published over 95 papers in international journals, conferences, patents, and book chapters. Her research focuses on wireless sensor networks, wireless body area networks, mobile communications, AI, IoT, information security, and computer graphics. Moolchand Sharma, PhD is an assistant professor in the Department of Computer Science and Engineering at the Maharaja Agrasen Institute of Technology, Guru Gobind Singh Indraprastha University, New Delhi, India. He has published four books and several book chapters, as well as numerous scientific research publications in reputed international journals and conferences. His research areas include artificial intelligence, nature-inspired computing, security in cloud computing, machine learning, and search engine optimization. Dac-Nhuong Le, PhD is an associate professor of Computer Science and Dean of the Faculty of Information Technology at Haiphong University, Vietnam with over 20 years of teaching experience. He has authored and edited over 35 books and numerous articles in international journals and conferences. His areas of research include soft computing, network communication, security and vulnerability, network performance analysis and simulation, cloud computing, IoT, and image processing for biomedicine.
Kotlin Mastery
Enhance your programming toolkit and build robust applications by mastering Kotlin. This book connects Java and Kotlin through side-by-side code samples and practical demonstrations. Java programmers and up-and-coming developers seeking to learn Kotlin need to do so with confidence. Starting with the fundamentals of basic syntax, this book will cover data types, variables, control flow statements. From there move on to advanced topics like object-oriented programming concepts with null safety, lambdas, functions, inheritance and coroutines. Additionally, you’ll delve into practical applications such as designing custom domain-specific languages, working with Kotlin Multiplatform, and leveraging reactive extensions. With numerous hands-on exercises and real-world examples, you'll gain the expertise needed to explore advanced projects. What You Will Learn Explore object-oriented and functional programming with Kotlin to create modular code. Review Kotlin’s techniques for error handling and exception management. Implement Kotlin coroutines for efficient concurrency and asynchronous task management. Design custom domain-specific languages and use the Kotlin standard library for string manipulation and file handling. Who This Book is for Java developers and programmers looking to master Kotlin. 1. Introduction to Kotlin Programming.- 2. Fundamentals of Kotlin Programming.- 3. Functions in Kotlin.- 4. Object-Oriented Programming with Kotlin.- 5. Error Handling and Exceptions.- 6. Collections and Generics.- 7. Kotlin Coroutines.- 8. Kotlin DSL (Domain-Specific Language).- 9. Kotlin Standard Library.- 10. Testing in Kotlin.- 11. Kotlin Reactive Extensions (Rx).- 12. Working with APIs and Networking.- 13. Advanced Kotlin Programming.- 14. Data Analysis with Kotlin.- 15. Kotlin Multiplatform.
Large Language Models Ops for Finance
Explore emerging technologies and the evolving role of AI in finance. Geared toward finance professionals, this book will equip you with the knowledge and tools to harness the power of Large Language Models (LLMs), ensuring you stay ahead in an increasingly AI-driven industry. Highlighting the benefits and challenges of LLMs in financial contexts, the book starts with the necessary infrastructure setup, covering both hardware and software requirements. It offers a balanced discussion on cloud versus on-premises solutions, enabling you to make informed decisions based on their specific needs. Training and fine-tuning LLMs are critical components of effective deployment, and this book offers best practices, from data preparation to advanced fine-tuning techniques. It also delves into deployment strategies, with practical advice on building deployment pipelines, monitoring performance, and optimizing operations. Ensuring data privacy and security is paramount in finance, so you’ll take a close look at maintaining compliance with regulations while safeguarding sensitive information. You’ll also examine the integration of LLMs into existing financial systems, with real-world case studies and strategies for API development and real-time data processing. Monitoring and maintenance are crucial for long-term success, and the book outlines how to manage performance metrics, handle model drift, and ensure regular updates. Large Language Models Ops for Finance is your essential guide to discovering the transformative potential of LLMs in the finance industry. What You Will Learn ● Review LLMs and their applications in finance. ● Set up the infrastructure for training and deploying LLMs. ● Apply best practices for fine-tuning and maintaining LLMs. ● Employ techniques for integrating LLMs into existing financial systems Who This Book Is For AI and ML engineers, data scientists, and finance professionals interested in implementing and managing large language models within the finance industry. Chapter 1: Introduction to Large Language Models in Finance.- Chapter 2: Infrastructure Setup for LLMs.- Chapter 3: Training and Fine-Tuning LLMs.- Chapter 4: Deployment Strategies for LLMs.- Chapter 5: Ensuring Data Privacy and Security.- Chapter 6: Integrating LLMs into Financial Systems.- Chapter 7: Monitoring and Maintenance of LLMs.- Chapter 8: Future Trends in LLM Ops for Finance.
Nanobiotechnology
Explore the integration of nanotechnology with artificial intelligence (AI) and the Internet of Things (IoT), focusing on advancements, applications, and future prospects in the field. This book highlights the fusion of cutting-edge technologies with biological and nanomaterials, emphasizing their role in transforming industries such as medicine, environmental science, and manufacturing. This book delves into the fundamentals of Nano-Biotechnology, starting with its historical evolution and foundational concepts. It explores the various types of nanomaterials, such as quantum dots, polymeric nanoparticles, and metal nanoparticles, detailing their properties and applications in fields such as drug delivery, diagnostics, and catalysis. Cellular nanostructures, biomolecular motors, and bio-inspired nanostructures are discussed, alongside methods for nanomaterial synthesis, including physical, chemical, and biological approaches. A focus on AI and IoT integration is woven throughout, highlighting their roles in optimizing nanomaterial properties, synthesis processes, and applications. The book further explores nanomaterial characterization techniques, nanomedicine, water remediation, MEMS/NEMS, and nanocatalysis, while also addressing crucial topics such as environmental impact, ecotoxicology, and regulatory frameworks. Each chapter presents advanced technological insights, from nanobiocatalysts to thin films and self-assembled nanostructures, all within the context of AI and IoT-driven advancements. You will gain a deep understanding of the interdisciplinary nature of Nano-Biotechnology, the implications of AI and IoT integration, and the ethical, environmental, and societal considerations shaping the future of this rapidly evolving field. The book offers valuable perspectives on emerging trends and equips readers with insights necessary for both academic and practical applications of Nano-Biotechnology. You Will Understand the key concepts, classification, properties, and applications of various nanomaterials in fields like medicine, diagnostics, and catalysis Gain insights into the physical, chemical, and biological methods of nanomaterial synthesis as well as advanced techniques Discover how Nano-Biotechnology is being applied to multiple sectors and MEMS/NEMS systems, and learn about the challenges and future trends Who Is This Book For Readers with a basic to intermediate understanding of nanotechnology, biotechnology, or related fields will benefit from this book. A general familiarity with concepts like AI, IoT, and their applications in scientific disciplines will also be helpful. Chapter 1: Introduction to Nano-Biotechnology.- Chapter 2: Types of Nanomaterials and Their Properties.- Chapter 3: Cellular Nanostructures and Biomolecular Motors.- Chapter 4: Synthesis of Nanomaterials.- Chapter 5: Characterization of Nanomaterials.- Chapter 6: Thin Films and Colloidal Nanostructures.- Chapter 7: Self-Assembly and Nanovesicles.- Chapter 8: Nanoparticles for Drug Delivery.- Chapter 9: Nanoparticles for Diagnostics and Imaging.- Chapter 10: Nanobiocatalysts and Their Applications.- Chapter 11: Environmental and Health Impacts of Nanomaterials.- Chapter 12: Ecotoxicology and Life Cycle Assessment.- Chapter 13: Nanomaterials in Catalysis.- Chapter 14: Nanotechnology in Medicine.- Chapter 15: Nanotechnology in Food Science.- Chapter 16: Nanotechnology for Water Remediation and Purification.- Chapter 17: MEMS and NEMS Based on Nanomaterials.- Chapter 18: Safety and Regulation of Nanomaterials.- Chapter 19: Genotoxicity and Cytotoxicity of Nanomaterials.- Chapter 20: Future Directions in Nano-Biotechnology.
GovOps with Microsoft Power Platform and Copilot
In an era of tightening budgets and rising citizen expectations, government agencies must modernize or risk obsolescence. This book provides a comprehensive, hands‑on roadmap for public sector leaders, architects, and developers to harness Microsoft Power Platform’s low‑code and AI capabilities with Power Apps, Power Automate, Power BI, Power Pages, AI Builder, Copilot, and Dataverse. This book lays out the case for low‑code modernization, demonstrates how to assess organizational readiness, and introduces governance and CoE best practices. Readers will walk away with repeatable frameworks, proven templates, and scripts to accelerate digital transformation in any government setting to foster transparency, efficiency, and citizen‑first service delivery. What You Will Learn Core Platform Deep Dive: Unpacks each Power Platform component with architecture patterns, step‑by‑step tutorials, and design guidelines using official Microsoft icons. Sector‑Specific Use Cases: Shares rich, real‑world examples from licensing and permitting to emergency response coordination, complete with workflows, code samples, and architecture diagrams. Advanced AI & Copilot Integrations: Shows how to train custom AI models, implement Copilot–powered natural‑language generation, and embed responsible AI with human‑in‑the‑loop designs. Operational Excellence, ALM & the Road Ahead: Covers CI/CD pipelines, environment management, security/DLP policy enforcement, accessibility, and next‑gen Copilot trends. Who This Book is For This book is for IT leaders, solution architects, citizen developers, line‑of‑business analysts, and public sector project managers looking to modernize government services. Readers should have some familiarity with Microsoft 365 or basic low-code. Chapter 1: Introduction to Government Modernization.- Chapter 2: Overview of Microsoft Power Platform.- Chapter 3: Planning a Government Low‑Code Strategy.- Chapter 4: Building End‑to‑End Solutions.- Chapter 5: Integrating AI and Co-Pilot.- Chapter 6: Deployment & Governance.- Chapter 7: Facilitating Government Modernization through Use Cases.- Chapter 8: Best Practices & Frameworks.- Chapter 9: The Road Ahead.- Chapter 10: Resources & Templates.- Chapter 11: Azure AI + AI Builder High-Level AI Model Development.- Chapter 12: Copilot Studio In-Depth Tutorial – Bots, Prompts & Custom Skills.- Chapter 13: Low-Code + Pro-Code Fusion – When to Extend with Azure Functions.- Chapter 14: Secure External API Integrations in Government Applications.- Chapter 15: Data Governance & Sovereignty with Dataverse and Azure.- Chapter 16: Making Power Platform Solutions Run Better.- Chapter 17: Monitoring & Logging with Azure Monitor and Power Platform Admin Center.- Chapter 18: Disaster Recovery & Business Continuity Planning.- Chapter 19: The Future of Digital Government – Trends to Watch.- Chapter 20: Developing a Culture of Low-Code Innovation in Government Sector.
Integration of Federated Learning and Blockchain for Smart Cities
Stay ahead of the curve in urban innovation with this essential guide that provides a comprehensive roadmap for federated learning and blockchain to build secure, intelligent, and efficient smart city ecosystems. As cities grow smarter, the demand for secure, decentralized, and privacy-preserving technologies is greater than ever. This book explores how federated learning and blockchain are transforming urban landscapes by enabling intelligent, secure, and efficient systems. By combining the power of decentralized machine learning with the transparency and security of blockchain, this book provides a roadmap for tackling challenges in urban mobility, energy management, public safety, and healthcare, delving into theoretical frameworks, architectural designs, security considerations, and real-world case studies to illustrate the impact of these technologies. This book serves as a comprehensive guide for researchers, industry professionals, and policymakers seeking to understand, implement, and innovate within smart city ecosystems. Readers will find the volume: Explores the synergy between federated learning and blockchain, offering cutting-edge solutions for smart city challenges;Addresses critical issues of data privacy, decentralized AI, and secure digital infrastructure in urban environments;Features practical case studies on smart transportation, energy management, healthcare, and governance;Provides a forward-looking perspective on how emerging technologies will shape the cities of tomorrow. Audience Academics, researchers, industry professionals, and policymakers working in the fields of artificial intelligence, machine learning, blockchain, IoT, cybersecurity, smart city planning, and urban technology development. Krishna Kant Singh, PhD is the Director at the Delhi Technical Campus, Greater Noida, India. He has authored 25 books and over 160 research papers in international journals. He is an associate editor of IEEE Transactions on Computational Social Systems, and Senior editor of IEEE Access. His research interests include machine vision, remote sensing, deep learning, and generative AI. Akansha Singh, PhD is a professor in the School of Computer Science, Engineering, and Technology at Bennett University, Greater Noida, India, with over 18 years of teaching and research experience. She has published over 100 research papers and authored over 30 books in advanced areas of computer science. Her expertise spans image processing, deep learning, machine learning, remote sensing, and IoT, with a strong focus on AI-driven solutions for healthcare and environmental sustainability. Mahesh T.R., PhD is the Program Head of the Department of Computer Science and Engineering in the School of Engineering and Technology, at Jain (Deemed-to-be University), Bengaluru, India. He has published over 180 research articles in international and edited several books. His research interests include image processing, machine learning, deep learning, artificial intelligence, IoT, and data science.
The AI Product Playbook
A comprehensive guide for aspiring and practicing AI product managers The AI Product Playbook: Strategies, Skills, and Frameworks for the AI-Driven Product Manager, by Dr. Marily Nika and Diego Granados, is a practical guide designed to empower product managers to effectively build, launch, and manage successful AI-powered products. This playbook bridges the gap between complex AI concepts and real-world product management, offering actionable frameworks and strategic insights tailored to non-technical professionals. Drawing on their extensive industry experience, the authors guide you in understanding the three essential AI Product Manager personas: AI Experiences PM, AI Builder PM, and AI-Enhanced PM. This framework empowers you to identify your own strengths, focus your skill development, and chart a clear career path in the evolving AI job market. The AI Product Playbook demystifies the full spectrum of AI product development, with a special focus on today’s most transformative technologies like Generative AI and Large Language Models (LLMs). Alongside this modern focus, you will build a strong foundation in the core paradigms of traditional machine learning, understand the complete data science lifecycle, and grasp the operational realities of MLOps. The book also provides actionable frameworks for ethical AI implementation, grounding these concepts in real-world case studies and practical examples. An essential, strategic guide for aspiring and experienced product managers, The AI Product Playbook delivers an effective roadmap to AI-driven product management and career advancement in the AI era. A comprehensive guide for aspiring and current AI product managers The AI Product Playbook: Strategies, Skills, and Frameworks for the AI-Driven Product Manager, by Dr. Marily Nika and Diego Granados, is a practical resource designed to empower product managers to effectively build, launch, and manage successful AI-powered products. This playbook bridges the gap between artificial intelligence theory and real-world product management, offering actionable learnings tailored to non-technical professionals. Drawing from extensive industry experience, Dr. Nika and Granados introduce the three essential AI product manager roles: AI Experiences PM, AI Builder PM, and AI-Enhanced PM. They offer guidance on developing skills crucial for each role and navigating common challenges in the workplace. Readers will also find valuable strategies for career growth, lifelong learning, and crafting a distinctive AI portfolio. Inside the book: Practical frameworks for discovering AI opportunities and aligning AI capabilities with business goalsA deep technical dive with clear explanations of foundational AI and machine learning concepts, including supervised learning, unsupervised learning, reinforcement learning, and generative AIGuidelines for ethical AI implementation, addressing bias, fairness, and compliance with AI regulationsStrategies for effective collaboration with cross-functional teams and enhancing productivity through AIInteractive exercises, action plans, checklists, templates, and quizzes designed to reinforce learning and build real-world skills Essential reading for aspiring and experienced product managers alike, The AI Product Playbook provides a roadmap to mastering AI-driven product management and advancing your career in the dynamic field of artificial intelligence. Dr. Marily Nika is an award-winning GenAI Product Leader at Google and one of the world's foremost AI educators, with over 13 years of experience building AI products at Google and Meta. She holds a PhD in machine learning and is an author, TED AI speaker, Harvard Business School fellow and co-founder of the AI Product Hub (www.aiproduct.com) which offers AI product management certifications. Diego Granados is a Product Leader with more than 6 years of experience bringing AI products to life in top tech companies in Silicon Valley. He holds an MBA from Duke University and an M.S. in C.S. focused on AI & ML from Georgia Tech and is co-founder of the AI Product Hub (www.aiproduct.com) which offers AI product management certifications.
Adaptive Artificial Intelligence
Master the next frontier of technology with this book, which provides an in-depth guide to adaptive artificial intelligence and its ability to create flexible, self-governed systems in dynamic industries. Adaptive artificial intelligence represents a significant advancement in the development of AI systems, particularly within various industries that require robust, flexible, and responsive technologies. Unlike traditional AI, which operates based on pre-defined models and static data, adaptive AI is designed to learn and evolve in real time, making it particularly valuable in dynamic and unpredictable environments. This capability is increasingly important in disciplines such as autonomous systems, healthcare, finance, and industrial automation, where the ability to adapt to new information and changing conditions is crucial. In industry development, adaptive AI drives innovation by enabling systems that can continuously improve their performance and decision-making processes without the need for constant human intervention. This leads to more efficient operations, reduced downtime, and enhanced outcomes across sectors. As industries increasingly rely on AI for critical functions, the adaptive capability of these systems becomes a cornerstone for achieving higher levels of automation, reliability, and intelligence in technological solutions. Readers will find the book: Introduces the emerging concept of adaptive artificial intelligence;Explores the many applications of adaptive artificial intelligence across various industries;Provides comprehensive coverage of reinforcement learning for different domains. Audience Research scholars, IT professionals, engineering students, network administrators, artificial intelligence and deep learning experts, and government research agencies looking to innovate with the power of artificial intelligence. P. Pavan Kumar, PhD is an associate professor in the Department of Artificial Intelligence and Data Science at the ICFAI Foundation for Higher Education, Hyderabad, Telangana, India. He has published more than 20 scholarly peer-reviewed research articles in international journals and two Indian patents. His research interests include real-time systems, multi-core systems, high-performance systems, and computer vision. Grandhi Suresh Kumar, PhD is an associate professor and Associate Dean of Academics in the School of Science and Technology at the ICFAI Foundation for Higher Education, Hyderabad, Telangana, India with more than ten years of experience. He has published one authored book, one edited book, one book chapter, and more than 15 articles. His research interests include intelligent manufacturing, robotics, sustainable energy solutions, CO2 capture, and applications of AI in mechanical engineering. Ajay Kumar Jena, PhD is an assistant professor and Associate Dean in the School of Computer Engineering at the Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India. He has published three books, seven book chapters, and 61 research papers in various international journals and conferences. His research interests include blockchain, object-oriented software testing, software engineering, data science, soft computing, and machine learning. Sandeep Kumar Panda, PhD is a professor and an Associate Dean in the School of Science and Technology at the ICFAI Foundation for Higher Education, Hyderabad, Telangana, India. He has published six books, several book chapters, and 80 articles in international journals and conferences. His research interests include blockchain technology, W3, metaverse, the Internet of Things, AI, and cloud computing. S. Balamurugan, PhD is the Director of Research, iRCS, an Indian technological research and consulting firm. He has published more than 100 books, 300 papers in international journals and conferences, and 300 patents. With 20 years of research experience using various cutting-edge technologies, he provides expert guidance in technology forecasting and decision-making for leading companies and startups.
Security-System Engineering
Das Anliegen des Buches ist es, das Wechselspiel zwischen geschäftlichen Anforderungen, geschäftlichen IT-Systemen und notwendigen Sicherheitsfunktionen strukturierter und methodischer zu erfassen. Hierzu wird die Herangehensweise verfolgt, etablierte System-Engineering Ansätze - wie etwa der ISO 15288 - auf das Ökosystem der Informationssicherheit zu übertragen. Informationssicherheit aus dem Kochbuch.- Security-System - Security und System.- Security-Systems-Engineering.- Business Kontext.- Security Kontext.- Security-Requirements.- Security-System Model.- Sicherheitsarchitektur.- Security Controls Management.- Security-Systems Management.
Datenschutzrechtliche Rollenzuweisungen
Die Arbeit evaluiert die praktische Effektivität und Schlüssigkeit des europäischen Datenschutzrechts in Bezug auf unterschiedliche Rollenzuweisungen. Um auf allgegenwärtige Strukturverschiebungen bei der Verarbeitung personenbezogener Daten und drohende Beeinträchtigungen für die Rechte Betroffener durch differenzierte Rollenzuweisungen zu reagieren, kommt der ganzheitlichen Fortentwicklung des Verantwortlichkeits- und Beteiligungsgefüges eine zentrale Bedeutung zu. Voraussetzung für vereinheitlichte Rollenzuweisungen auf europäischer Ebene ist die Entwicklung eines kohärenten Gesamtkonzepts, das sowohl die rechtlichen Voraussetzungen und Grenzen klar umreißt als auch allgemeingültige Regulierungsprinzipien festlegt. Nur ein im Kern harmonisierter Regelungsrahmen kann beteiligten Akteuren als Orientierungshilfe dienen, die – vorgeschaltet zur konkreten Einzelfallbetrachtung – dazu beiträgt, dass grundlegende Wertungen des europäischen Datenschutzrechts gewahrt werden. Einleitung.- Verarbeitung personenbezogener Daten im Strukturwandel.- Dimensionen des europäischen Datenschutzes.- Die gesetzlichen Grundlagen des die Rollenbilder betreffenden Normengefüges.- Einzelfallbezogene Rollenzuweisungen durch den EuGH.- Kritische Analyse der EuGH-Rechtsprechung.- Korrekturansätze und Gestaltungsspielräume unter dem bestehenden Regelungsgefüge.- Grundstrukturen und Musterfälle künftiger Rollenzuweisungen.- Schlussbetrachtung.
API Development with Laravel
API Development with Laravel is your quick start guide to understanding and developing APIs in Laravel. Concepts are presented in an easy-to-follow and digestable manner. The concepts are not only clearly explained but practical examples are used to show how they are implemented. During the course of this book, you’ll learn how to build a RESTful Payment Processing API of your own. The book is written in a straight-forward manner ensuring your time is not wasted. We will start with an a general introduction to APIs before focusing on RESTful APIs in particular. We then look at setting up our development environments after which, we will look at why Laravel is a tool of choice for API development, exploring Laravel concepts for API development. We'll then start the implementation of our project using concepts we have learned. Finally, we'll look at how to deploy our project. You Will Learn To: * Develop Laravel-powered RESTful APIs * Build a Payment Processing API * Test your APIs * Deploy your APIs * Document and version control your APIs * Make APIs secure with security best practices This Book Is For: Anyone interested in acquiring knowledge about API development. The ideal reader should possess the ability to navigate a computer's file system, as well as the skills to create, open, and manage files and folders. Additionally, familiarity with web browsers and the capability to navigate between different websites is essential. A willingness to use the command line and an understanding of basic programming concepts, particularly in PHP, is also recommended. Part I: Fundamentals of Lavavel APIs.- Chapter 1. Introduction To APIs.-Chapter 2. Laravel, Development And Test Tools Installation.- Chapter 3. Laravel For API Development.- Chapter 4. Laravel For API Development: Further Steps.- Part II: Payment Processor API Development.- Chapter 5. Magic Link and Dashboard Implementation.- Chapter 6. Endpoints Implementation and Documentation.- Chapter 7. Automated Functional Testing with EchoAPI.- Chapter 8. Webhook and Asynchronous Notifications Implementation.- Chapter 9. Deploying And Scaling Your API Using CapRover.
Securing the Enterprise
Cybersecurity is no longer just an IT issue; it is a business-critical function requiring executive oversight and strategic implementation. This book offers a practical approach to cybersecurity leadership, risk management, and frameworks such as NIST, MITRE ATT&CK, and Zero Trust. The book blends executive strategy with hands-on cybersecurity methodologies, providing a holistic understanding for CXOs, CISOs, and IT security professionals. By exploring real-world case studies and breaches, such as SolarWinds and Colonial Pipeline, this book equips you with proactive defense strategies, governance insights, and the technical knowledge required to secure enterprise infrastructures effectively. What You Will Learn * Align cybersecurity with business strategy and executive decision making * Cover practical implementation of frameworks such as NIST CSF, ISO 27001, and Zero Trust * Respond to cyber incidents and build a resilient security culture * Understand key cybersecurity principles, including threat intelligence and risk management * Study advanced cybersecurity topics, including AI-driven threats, ransomware, and cloud security Who This Book Is For Cybersecurity professionals, CISOs, CIOs, IT security architects, and risk managers; plus business executives, Chief Experience Officers (CXOs), board members, compliance officers, graduate students in cybersecurity Part 1: Foundations of Cybersecurity.- Chapter 1: Introduction to Cybersecurity.- Chapter 2: Core Cybersecurity Concepts.- Chapter 3: The Threat Landscape.- Part 2: The Role of Leaders in Cybersecurity.- Chapter 4: The Role of CXOs & Executive Leaders.- Chapter 5: The Role of the Board of Directors.- Chapter 6: The CISO Role & Responsibilities.- Chapter 7: Leadership & Communication.- Chapter 8: CISO Skills & Competencies.- Part 3: Cybersecurity Frameworks & Regulations.- Chapter 9: Key Cybersecurity Frameworks.- Chapter 10: Compliance & Regulations.- Chapter 11: Implementing a Security Program.- Part 4: Advanced Topics in Cybersecurity.- Chapter 12: Cloud Security.- Chapter 13: Security Information & Event Management (SIEM).- Chapter 14: AI & Machine Learning in Cybersecurity.- Chapter 15: IoT Security.- Chapter 16: Blockchain & Cryptocurrency Security.- Chapter 17: Zero Trust Architecture (ZTA).- Part 5: Cybersecurity Tabletop Exercises (TTXs) & Case Studies.- Chapter 18: Cybersecurity Tabletop Exercises (TTXs).- Chapter 19: Notable Cybersecurity Incidents & Lessons Learned.- Chapter 20: Future of Cybersecurity.- Chapter 21: Tabletop Exercise - A Critical Tool for Incident Preparedness.- Chapter 22: David vs. Goliath: Cybersecurity's Constant Struggle.
The Low-Code AI Maturity Model
Written from the perspective of an experienced IT expert, this book leverages a maturity model framework to guide organizations through each stage of adopting, securing, scaling, and tracking the value of low-code AI responsibly and efficiently. Unlike other works that focus only on AI’s technical aspects, this book boasts a practical roadmap for responsible AI adoption and provides a clear, structured maturity model that guides organizations from foundational steps to advanced, responsible AI practices. In a world where organizations are under pressure to innovate quickly and responsibly, this book provides a structured approach, addressing essential elements such as data management, governance, ethics and compliance in low-code AI environments. Each chapter represents a maturity level, from foundational to optimized, offering readers insights, practical steps and examples to support their journey. The Low-Code AI Maturity Model takes a comprehensive look into the transformative potential of low-code and AI. What You Will Learn * Identify, assess and mitigate risks to ensure stable and reliable AI deployments * Implement robust governance, aligning with compliance standards and ethical principles at each maturity stage * Evaluate the real business value and ROI of AI projects, empowering data-driven decision-making Who This Book Is For IT leaders, decision-makers, and technology enthusiasts interested in the transformative potential of low-code and AI Part 1: Leadership and Culture.- Chapter 1: Foundational: Leadership and Culture.- Chapter 2: Emerging: Leadership and Culture.- Chapter 3: Operationalized: Leadership and culture.- Chapter 4: Integrated Excellence: Leadership and Culture.- Part 2: Establishing Trust and Governance.- Chapter 5: Foundational: EstablishingTrust and Governance.- Chapter 6: Emerging: Establishing Trust and Governance.- Chapter 7: Operationalized: Establishing Trust and Governance.- Chapter 8: Integrated Excellence:Establishing Trust and Governance.- Part 3: Data Readiness and Security.- Chapter 9: Foundational: Data Readiness and Security.- Chapter 10: Emerging: Data Readiness and Security- Chapter 11: Data Readiness and Security: Operationalized Stage.- Chapter 12: Data Readiness and Security: Integrated Excellence Stage.- Chapter 13: The Journey Forward: Leadership in the Age of Low-Code AI.
IoT Product Development Using ESP32 Microcontrollers
Develop a comprehensive understanding of IoT product development using ESP32 microcontrollers. This book takes readers on a journey from sensor interface example to an ESP32-based product example where we discuss all aspects of a product including rapid prototyping, cloud interface, product provision, and device fleet management. We will start with an introduction to the ESP32 microcontroller series and discuss programming language options for the ESP32 platform. Next, we explore publishing sensor data to the cloud using the ESP32. This is followed by a review of using the ESP32 to pull data from a public source and display it using a visual aid. The next few chapters demonstrate the construction of a low-cost Bluetooth sensor node using the ESP32, data aggregation with the ESP32, where collect and publish data aggregated from low-power radio networks, and the development of edge devices using the ESP32. The final chapter shows how to build an ESP32-enabled product that publishes data to the cloud, giving you confidence to start building on your own. What You Will Learn · Learn about the rich and powerful features of the ESP32 family of microcontrollers · Get a thorough idea of rapid prototyping tools and techniques for IoT product development · Understand the various communication protocols and standards available for IoT product development Who Is This Book For Readers with some experience with electronics and at least one programming language will be able to make the most of this book. Chapter 1. Introduction to the ESP32 Platform.- Chapter 2. Building a Weather Station.- Chapter 3. Visual Aid for Air Quality.- Chapter 4. Building Bluetooth Products using ESP32.- Chapter 5. Low Power & Long Range Radios with ESP32.- Chapter 6. Building TinyML Products.- Chapter 7. Let’s Build a Product!.
AI Strategy and Security
AI will fundamentally change the way business is conducted across most industries. Organizations that excel at leveraging secure, responsible AI to advance their strategic objectives will have a distinct advantage. Those that do not may see their market share erode. This book provides a guide for organizations to integrate AI in alignment with the organization's strategic goals. The framework provides a roadmap for adopting secure, responsible, and resilient AI, from initial strategy development to ongoing operations that will help advance market leadership. Part one of the book discusses laying a solid foundation to ensure successful AI integration, beginning with developing an AI strategy aligned with strategic business objectives, such as product and service differentiation, market expansion, and process optimization. Part Two takes a deep dive into ensuring secure and safe AI adoption. It proposes a secure-by-design approach to AI development that considers AI-specific attack vectors and associated security practices throughout the AI lifecycle. Developing and deploying secure, responsible, and resilient AI is not a one-time effort. Therefore, Part Three discusses operationalizing AI and integrating it throughout the enterprise to ensure continued success. This section focuses on scaling AI applications and continuous improvement, including establishing metrics and conducting a post-deployment ROI evaluation. Finally, it discusses how to foster a culture of AI innovation and excellence, ensuring that AI becomes a way of doing business. What You Will Learn: * Develop an AI integration strategy aligned with the organization's strategic goals and objectives. * Incorporate a secure-by-design approach to AI integration that considers AI-specific attack vectors and applies traditional and AI-specific defense methods, such as adversarial development, model behavior monitoring, drift analysis, input validation and filtering, and output filtering. * Establish an AI governance and risk management framework to ensure ongoing compliance with applicable legislation, industry standards, organizational policies, and responsible AI principles. * Operationalize and scale AI applications to ensure resilient production usage and facilitate continuous improvement. * Foster a culture of AI innovation and excellence, ensuring that AI becomes a way of doing business. Who This Book is for: The primary audience includes business leaders, AI practitioners, AI executives, AI governance professionals, and cybersecurity leaders looking to integrate AI as a strategic differentiator and to enhance business operations. Higher education would be a secondary audience. Chapter 1, Strategy Development.- Chapter 2, Assess AI Readiness.- Chapter 3, The Team.- Chapter 4, Securing AI.- Chapter 5, Governance and Risks.- Chapter 6, Ensuring Responsible AI.- Chapter 7, Regulations and Standards.- Chapter 8, Operationalizing AI.- Chapter 9, Continuous Improvement.- Chapter 10, AI as a Way of Doing Business.- Chapter 11, The AI Adoption and Management Framework.
GitHub Copilot and AI Coding Tools in Practice
Learn the current state of generative AI coding tools like GitHub Copilot, what the underlying models mean, and how to use them across the full development life-cycle. Look ahead to the near future of AI-generated software and understand how software developers can stay relevant in the industry. Many companies have predicted that human coders will soon be redundant due to AI-generated code, but there is a big gap between the expectations and what is actually happening on the ground. A closer look at the current state of the tools and research in this area will offer realism and guidance to developers worried regarding redundancy. Close the gap between hype and practical applications by receiving context and clear technical information on usage, understanding, and deployment of these tools. What You Will Learn: * How to use coding and software AI tools * How software AI tools work * How software AI tools fit in an industry context * How to use AI tools across the SDLC – it's more than just faster coding Who This Book is For All software industry participants interested in mastering AI-generated code. Chapter 1: Current State of Play - The High Level View.- Chapter 2: Using an AI Coding Agent.- Chapter 3: Large Language Models - Under the Hood.- Chapter 4: Prompt Engineering with AI Coding Agents.- Chapter 5: Customizing and Extending Copilot.- Chapter 6: Security in the Time of Copilot.- Chapter 7: Designing Applications with Copilot.- Chapter 8: Infrastructure, DevOps and Monitoring with Copilot and AI.- Chapter 9: Databases and AI.- Chapter 10: Copilot and Data Science.- Chapter 11: Code Migrations and Refactoring.- Chapter 12: Testing Augmentation with AI.- Chapter 13: Management Challenges Introducing AI.- Chapter 14: Surviving as a Software Engineer.- Chapter 15: Introducing and Integrating Copilot in an Organization.
Creative Machines
Praise for Creative Machines “Creative Machines challenges the illusion of either/or—inviting us to embrace the transformative power of and. It’s a visionary call to dissolve the artificial boundaries between art and technology, the physical and digital, prose and code. This isn’t about machines becoming human— it’s about humans fully realizing our potential.” —HANNAH GELLER, Emmy-nominated Producer “This book hits at exactly the right moment. In an industry flooded with fast tech, Creative Machines asks the deeper questions: about artistry, AI, and where we actually want this to go.” —DANIEL ROWLAND, Oscar-winning, Grammy-nominated Audio Engineer and Producer “Creative Machines opens up a critical and often overlooked part of the AI conversation: how these tools are actually used by real people in creative workflows.” —MATEI ZAHARIA, CTO of Databricks and Professor at the University of California, Berkeley A BOLD AND EYE-OPENING JOURNEY INTO AI’S POWER TO TRANSFORM HUMAN CREATIVITY Creative Machines: AI, Art & Us, by renowned generative AI researcher and pioneer, Maya Ackerman, is an exciting and original new discussion of the rise of creative artificial intelligence. She takes you on a journey that begins with the earliest AI trailblazers and concludes with examinations of the contemporary, cutting-edge tools shaping music, art, and human imagination today. Ackerman demolishes the hype and misinformation that surrounds generative AI to reveal the opportunities and dangers that the technology actually presents. She draws on psychology, neuroscience, and her own data-driven research to explain how generative artificial intelligence can enhance the brilliance and expose the blind spots in human creativity. Creative Machines is an exciting and practical walk-through of the creative and imaginative dimensions of our humanity—our ingenuity, biases, intelligence, and identities—and how we can build on them using AI. It’s a must-read for developers, founders, ethicists, artists, business leaders, and anyone else interested in harnessing the latest developments in tech to discover new ways of doing business, creating art, and explaining the world around us. A bold and thought-provoking journey into AI's power to transform human creativity In Creative Machines: AI, Art & Us, world-renowned AI researcher and generative AI pioneer, Maya Ackerman, takes you on a thrilling journey into the rise of creative AI, from its earliest pioneers to the cutting-edge tools shaping music, art, and human imagination today. Ackerman cuts through the hype, revealing the true capabilities and limitations of generative AI while championing its potential to amplify human creativity rather than replace it. Drawing on psychology, philosophy, and her own cutting-edge research, she reveals how generative AI exposes both the brilliance and the blind spots of human society—our ingenuity, our biases, our assumptions about intelligence and identity. The book contains: The hidden history and explosive growth of AI-generated creativityExplorations of the true capabilities and limitations of creative AIA visionary framework for using AI as a tool to enhance, rather than hinder, human creativityA bold new perspective on AI ethics and why fixing AI is not enough Perfect for entrepreneurs, tech leaders, developers, ethicists, and creative professionals, Creative Machines offers deep insights, compelling stories, and a visionary perspective on AI's impact on human society. An essential read for anyone doing their best to navigate the rapidly evolving landscape of generative AI. MAYA ACKERMAN, PHD, is an internationally renowned leader in generative AI, pioneering the next chapter of creativity. As CEO and Co-Founder of WaveAI, one of the earliest generative AI startups, she has enabled millions to explore new frontiers in creative expression through AI. An Associate Professor at Santa Clara University, Dr. Ackerman is widely known for her research on AI and creativity. Dr. Ackerman’s insights have been featured in NBC News, NPR, Forbes, and more. Her work champions the role of AI in amplifying—rather than replacing—human creativity.
Language Models kompakt
Sie möchten in die Welt der Large Language Models eintauchen? Dieses handliche Buch hilft Ihnen, das nötige Grundlagenwissen aufzubauen, um das Innenleben von LLMs zu verstehen und erste praktische Erfahrungen zu sammeln. Es führt Schritt für Schritt in die Sprachmodellierung ein, beginnend mit Machine Learning und neuronalen Netzen über RNNs und Transformern bis zu aktuellen LLM-Architekturen. Das Buch unterstützt Sie dabei:die mathematischen Grundlagen des Machine Learnings und der neuronalen Netze zu verstehen und zu beherrschendrei Architekturen von Language Models in Python zu erstellen und zu trainierenein Transformer-Sprachmodell von Grund auf in PyTorch zu programmierenmit LLMs zu arbeiten und effektive Prompt-Engineering- und Feinetuning-Techniken kennenzulernenHalluzinationen zu vermeiden und Modelle zu bewertenÜber den Autor:Andriy Burkov hat einen Doktortitel in Künstlicher Intelligenz und ist ein anerkannter Experte für Machine Learning und Natural Language Processing. Bei Fujitsu und Gartner hat er zahlreiche produktionsreife KI-Projekte in verschiedenen Geschäftsbereichen erfolgreich geleitet. Seine Bücher wurden in zwölf Sprachen übersetzt und werden als Lehrbücher an vielen Universitäten weltweit verwendet. Seine Arbeit hat Millionen von Praktikern und Forschern im Bereich Machine Learning weltweit beeinflusst.
Language Models kompakt
Der schnellste Weg, um die Mechanismen von LLMs zu verstehen - Dieses Buch ist eine sehr komprimierte und gleichzeitig gut verständliche Einführung in die Entwicklung von Large Language Models - Ideal für alle, die sich schnell und fundiert in die Grundlagen von LLMs einarbeiten wollen - Vom Bestseller-Autor Andriy Burkov, der in seiner renommierten »Hundred-Page«-Reihe zu Machine-Learning-Themen Konzepte besonders klar und knapp erklärt Sie möchten in die Welt der Large Language Models eintauchen? Dieses handliche Buch hilft Ihnen, das nötige Grundlagenwissen aufzubauen, um das Innenleben von LLMs zu verstehen und erste praktische Erfahrungen zu sammeln. Es führt Schritt für Schritt in die Sprachmodellierung ein, beginnend mit Machine Learning und neuronalen Netzen über RNNs und Transformern bis zu aktuellen LLM-Architekturen. Bestseller-Autor Andriy Burkov – bekannt für seine »Hundred-Page«-Reihe zu Machine-Learning-Themen – macht die komplexen Ideen leicht zugänglich, indem er gut verständliche Erklärungen der Mathematik, zahlreiche Illustrationen und den Python-Code ausgewogen einsetzt. Auf der Website zum Buch finden Sie direkt ausführbare Codeschnipsel und PyTorch-Implementierungen in Jupyter Notebooks, die die Konzepte perfekt veranschaulichen. Das Buch unterstützt Sie dabei: - die mathematischen Grundlagen des Machine Learnings und der neuronalen Netze zu verstehen und zu beherrschen - drei Architekturen von Language Models in Python zu erstellen und zu trainieren - ein Transformer-Sprachmodell von Grund auf in PyTorch zu programmieren - mit LLMs zu arbeiten und effektive Prompt-Engineering- und Feinetuning-Techniken kennenzulernen - Halluzinationen zu vermeiden und Modelle zu bewerten
Prompt Engineering für Large Language Models
LLM-Anwendungen effektiv steuern: von der Prompt-Optimierung bis zur Workflow-IntegrationLLMs als leistungsstarke Bausteine für Anwendungen nutzenDen richtigen Prompt und Kontext für nützliche Ergebnisse gestaltenVon der Erfahrung der GitHub-Copilot-Entwickler profitierenFortgeschrittene Konzepte wie Conversational Agency und Workflow-Steuerung meisternLarge Language Models (LLMs) revolutionieren die Welt. Sie bieten die Möglichkeit, Aufgaben zu automatisieren und komplexe Probleme zu lösen. Eine neue Generation von Softwareanwendungen nutzt diese Modelle als zentrale Bausteine und erschließt in praktisch allen Bereichen völlig neues Potenzial. Um zuverlässig auf diese Funktionen zugreifen zu können, sind jedoch neue Fähigkeiten erforderlich.Mit diesem Buch eignen Sie sich die Kunst und die Techniken des Prompt Engineering an und schöpfen die Möglichkeiten von LLMs voll aus.Die Branchenexperten John Berryman und Albert Ziegler erklären, wie man effektiv mit KI kommuniziert und Ideen in ein sprachmodellfreundliches Format umwandelt. Durch das Erlernen der konzeptionellen Grundlagen und der praktischen Techniken erwerben Sie das Wissen und die nötige Sicherheit, um die nächste Generation von LLM-basierten Anwendungen zu entwickeln.Aus dem Inhalt:Verstehen Sie die LLM-Architektur und erfahren Sie, wie Sie am besten mit ihr interagieren können.Entwerfen Sie eine umfassende Strategie zur Erstellung von Prompts für eine Anwendung.Sammeln, sortieren und präsentieren Sie Kontextelemente, um eine effiziente Eingabeaufforderung zu erstellen.Erlernen Sie spezifische Techniken, um Prompts zu erstellen, wie Few-Shot-Prompting, Chain-of-Thought-Prompting und RAG.Leseprobe (PDF-Link)Über die Autoren: John Berryman ist Gründer von Arcturus Labs, einem Unternehmen, das sich auf die Entwicklung von LLM-basierten Anwendungen spezialisiert hat. Er war einer der ersten Entwickler bei GitHub Copilot und arbeitete dort an Chat- und Code-Vervollständigungsfunktionen. John ist außerdem Suchmaschinenexperte und Autor des Fachbuchs „Relevant Search“ (Manning).Albert Ziegler ist Head of AI beim KI-Cybersicherheitsunternehmen XBOW. Als einer der Gründungsentwickler von GitHub Copilot, dem ersten erfolgreichen LLM-Produkt im industriellen Maßstab, entwarf er dessen Systeme für die Modellinteraktion und das Prompt Engineering.
Becoming Quantum Safe
“The book Becoming Quantum Safe is a timely and essential guide for business and technology leaders. As quantum computing accelerates, the risks to today’s cryptographic systems are no longer theoretical. This book offers practical strategies and a clear roadmap to help organizations navigate the quantum era with confidence and build a secure digital future.” —ARVIND KRISHNA, CEO and Chairman, IBM A practical guide to navigating cryptographic challenges in the era of quantum computing. Becoming Quantum Safe: Protect Your Business and Mitigate Risks with Post-Quantum Cryptography and Crypto-Agility is a definitive, pragmatic guide designed for CISOs, CTOs, CIOs, CROs, CCOs, CDOs, DPOs, security leaders, and technology executives who need to understand and act on the quantum computing threat to current cryptography. This comprehensive playbook delivers step-by-step strategies to transition to Post-Quantum Cryptography (PQC)—ensuring your organization remains secure, compliant, and resilient in the quantum era. Authored by leading experts in cybersecurity, cryptography, and quantum technologies, this book demystifies the quantum threat, explains the vulnerabilities in today’s encryption, and provides a clear, actionable roadmap to achieve crypto-agility and implement quantum safe cryptography. What You Will Learn: How Quantum Computing Threatens Current Encryption Understand the real risks quantum computing poses to RSA, ECC, and other widely used encryption. Gain explanations of Shor’s Algorithm, Grover’s Algorithm, and how they impact classical cryptography.Practical Crypto-Agility Strategies Learn how to build a crypto-agile enterprise—one that can rapidly adopt, test, deploy, and manage new cryptographic standards without disrupting business operations.A Roadmap to Post-Quantum Cryptography (PQC) Adoption Follow a proven, step-by-step framework to transition from classical to quantum safe cryptography. Identify key milestones, address operational challenges, and implement solutions that safeguard data, operations, and digital trust.Learning from Real-World Enterprises Across Industries Insights from global enterprises in banking, financial services, government, telecommunications, healthcare, and retail embarking on their journey to quantum safe. A practical guide to navigating cryptographic challenges in the era of quantum computing. Becoming Quantum Safe: Implementing Post-Quantum Cryptography to Mitigate Risks and Protect Your Business is a is a definitive, pragmatic guide designed for CISOs, CTOs, CIOs, CROs, CCOs, CDOs, DPOs, security leaders, and technology executives who need to understand and act on the challenge posed by quantum computing to current cryptography. This comprehensive playbook delivers step-by-step strategies for transitioning to Post-Quantum Cryptography (PQC)—ensuring your organization remains secure, compliant, and resilient in the quantum era. Authored by leading experts in cybersecurity, cryptography, and quantum technologies, this book demystifies the quantum threat, explains the vulnerabilities in today's encryption, and provides clear, actionable guidance to achieve crypto-agility and implement quantum-safe cryptography. What You Will Learn: What is Quantum Computing and how it Threatens Current Encryption Understand the basics of quantum computing and the challenges it poses to RSA, ECC, and other widely used encryption. Gain explanations of Shor's Algorithm, Grover's Algorithm, and how they impact classical cryptography.Practical Crypto-Agility Strategies Learn how to build a crypto-agile enterprise—one that can rapidly adopt, test, deploy, and manage new cryptographic standards without disrupting business operations.A Roadmap to Post-Quantum Cryptography (PQC) Adoption Follow a proven, step-by-step framework to transition from classical to quantum-safe cryptography. Identify key milestones, address operational challenges, and implement solutions that safeguard data, operations, and digital trust. Learn about the consortia work that brings together players in the ecosystem and how one can leverage the work being done to accelerate the quantum safe journey.Case Studies Across Industries See how global leaders in banking, financial services, government, telecommunications, healthcare, and retail are adopting post-quantum cryptography to mitigate risks, achieve compliance, and future-proof their security infrastructure. Why This Book Matters Now: The quantum threat to encryption is real and time-sensitive. Quantum computers will render today's encryption obsolete, exposing sensitive data, customer trust, and business continuity. Regulatory pressures are rising. Governments and standards bodies across the globe are mandating quantum-safe transitions.Organizations that embrace crypto-agility today will lead the future, maintaining a secure competitive edge in a quantum-powered world. JAI SINGH ARUN spearheads global business strategy, product management, engineering, and go-to-market execution for IBM Quantum Safe. RAY HARISHANKAR is an IBM Fellow in the Quantum team. He leads business and technical strategy for IBM Quantum Safe. WALID RJAIBI is a Distinguished Engineer and Chief Architect for Quantum Safe at IBM Research. He leads innovations to make the world quantum safe.
The Ethics of Artificial Intelligence
The Ethics of Artificial Intelligence discusses the need for ethics accompanying developments in artificial intelligence, from the point of view of different disciplinary fields and sectors of activity. Artificial intelligence is profoundly restructuring our practices, creating new methods and significantly influencing the way we think and interact, at the level of individuals, organizations and societies, whether in our private, public or professional lives. This book begins with a rather conceptual approach, particularly focusing on the possible future of AI. It then highlights the urgent need to establish an ethical framework for the uses associated with AI, illustrating two booming sectors of activity. Finally, it discusses the ethics of AI in professional sectors that are undergoing major changes because of the digitization of their activities. Franck Debos is a lecturer in SIC at the Université de Nice Côte d'Azur, France. His research interests include issues associated with the ethics of AI, smart cities and digital uses.
Show AI--Don't Tell It
Praise forSHOW AI—DON’T TELL IT “Finally, a playbook that shows how to unlock AI’s power with business leaders, not just engineers, and demystifies the path from vision to real value.” —MARY SHEA, PHD, Former Principal Analyst at Forrester, Co-Founder & Chief Growth Officer at Meerkat “Her step-by-step methodology is the essential AI guide for driving collaborative, secure innovation, fast.” —ROB BENCE, VP of Technology & Cybersecurity at Tepper Sports and Entertainment, Owners of the Carolina Panthers “Critical resource for business leaders—this book fills in all the gaps between LLMs and making money!” —CHRIS GERMANN, Advisor to CMOs, Independent Consultant, Former Gartner VP, CIO Research Program “If you want to turn skeptics into champions, show them exactly how AI changes the game for your business.” —GREG NICHOLS, President of Technology Partners, AI Investor “Dr. Lisa delivers the field guide for leaders ready to secure the future by pairing advanced technology with courageous human leadership.” —JULIE VIDA, Retired Naval Commander, Cybersecurity Board Director, Former Splunk Chief Strategy Advisor “Every services partner chasing AI deals needs a blueprint like this for turning strategy into action and pipeline into revenue.” —JUSTIN SLAGLE, Former Microsoft Director, Global Systems Integrators, Founder & CEO of The Partner Masters The secret to AI adoption? Stop explaining the tech—help your organization visualize business success. Stakeholders don't invest in AI because they understand the tech—they invest when its business impact is clear and undeniable. In Show AI—Don't Tell It, AI executive and business strategist Dr. Lisa Palmer reveals how to use visual storytelling to make AI's value tangible, turning complex ideas into clear business outcomes that drive buy-in, adoption, and scale. Instead of vague theories and hype, this book provides clear frameworks, practical tools, and proven visualization techniques to help leaders secure funding, accelerate implementation, and maximize AI's impact. Applying her Bold AI Leadership Model, Dr. Palmer lays out a structured approach to AI success: Mindset: The four Applied AI Guiding Principles—Business Value, Speed with Rigor, Simplicity, and Human-Centricity—keep AI initiatives focused, efficient, and impactful.Strategic Priorities: The five AI Success Pillars—Value Creation, Customer-Centricity, Collaborative Teams, Cultural Shifts, and Data as a Strategic Asset—ensure AI drives measurable business results.Practical Tools: The Visualization Tool Decision Framework, featuring over 20 strategic visualization tools, helps leaders simplify complexity, overcome resistance, and communicate AI's impact with clarity and confidence. A must-read for executives, business leaders, and AI practitioners, Show AI—Don't Tell It provides the mindset, strategy, and tools needed to translate AI's potential into tangible value. Whether you're seeking stakeholder buy-in, funding approval, or faster adoption, this book shows you exactly how to use visual storytelling to accelerate business success with AI. DR. LISA PALMER is an Applied AI Executive Advisor, global keynote speaker, and the founder of an AI venture blending cutting-edge AI software with human expertise. Her unique value lies in having been a technology buyer, seller, advisor, and researcher—giving her a 360-degree perspective on how to turn AI into practical, profitable, people-friendly results.
Rechnernetze (8. Auflg.)
Ein einführendes Lehrbuch in 8. Auflage aus dem September 2025.Dieses einführende Lehrbuch für Studierende der Informatik und ingenieurwissenschaftlicher Studiengänge an Hochschulen und Berufsakademien vermittelt praxisnah und leicht verständlich die Grundlagen der Netzwerktechnik und der Netzwerkarchitektur. Es erläutert die Voraussetzungen, die Funktionsweise und die technischen Hintergründe von Computernetzwerken.Das Buch befähigt nicht nur zur Beurteilung der Technik, sondern hilft auch, praktische Abwägungen und Entscheidungen bei der Netzwerkplanung zu treffen. Es zeigt neben den Basiskomponenten, Übertragungsverfahren und Verbindungskomponenten auch strategische Aspekte, Trends und zukünftige Entwicklungslinien und vermittelt die Grundlagen zu Strategien und Methoden der Computervernetzung.Neu in der achten Auflage:Neue Transportprotokolle und Sicherheit in Transportkontrollen: Transport Layer Security (TLS), QUIC; Erweiterung Routing-Protokolle: Border Gateway Protocol (BGP); Sicherheit bei der Namensauflösung: DNS über HTTPS; neuer WLAN-Standard: Wifi7; Trends im Ethernet: automotive Ethernet, Time Sensitive Networking; Standards im und Organisation des Internets.Auf plus.hanser-fachbuch.de finden Sie zu diesem Titel digitales Zusatzmaterial: Lehrvideos, Quizzes zur Lernkontrolle, Mind-Maps der wichtigsten Konfigurationsbefehle für Cisco Router/Switches und die Lösungen zu den Aufgaben.