Computer und IT
PII Minimization Handbook
This book is a thorough and practical guide to minimizing personally identifiable information (PII) in every conceivable use case across Finance, Healthcare, Insurance, Legal, Marketing, HR, and Government. Most data protection laws and regulations require that businesses only use as much PII as is required for each specific processing purpose. In some cases, processing is only permitted when the data is fully anonymized. Hence, PII Minimization describes a spectrum from redacting very few, if any, direct identifiers to full anonymization. It is woefully unclear what exactly is required in terms of PII minimization. The feasibility and the degree of PII minimization crucially depend on what personal identifiers are present in the data set to be processed as well as the use case for processing it. Industry- and use-case-specific PII-Minimization Standards supplies expert insights from academia as well as the seven industries to be covered. These experts clarify what personal identifiers are commonly present in the data sets collected by or otherwise available to them, what use cases for data processing are prevalent in their industry, and which personal identifiers are (un)necessary for each use case. The book also features companies that are developing technological solutions to solve the difficult problem of data minimization. The practical insights to be gained here are how to achieve data minimization in specific use cases and with high accuracy to meet the regulatory requirements. As an example, for the development of facial recognition software, images of human faces must be used in machine-identifiable form. However, today’s technology can modify facial images for other use cases in such a way that they remain identifiable by human viewers but prevent the identification by automated systems. You Will: Explore the range of techniques for minimizing PII, from basic data reduction strategies to complete anonymization.Examine AI-specific regulations and their implications for data minimization, focusing on the most influential frameworks.Discuss the inherent challenges faced by general-purpose AI systems in implementing data minimization due to their extensive data needs and broad applications.Define key terms and concepts related to PII minimization technologies.Overview current and emerging technologies for minimizing PII in structured data, addressing their potential impacts and limitations.Explore methods and challenges in minimizing PII in unstructured data.Review data minimization in different industries and use cases. Who This Book is for: Data protection regulators as well as risk officers, privacy and data protection officers, product leaders, cybersecurity officers, information officers, and data leaders within organizations operating in Finance, Healthcare, Insurance, Legal, Marketing, HR, and Government that collect or process PII for purposes that require certain personal identifiers to be removed or obfuscated to meet data minimization requirements. The book is also for regulators developing actionable data minimization standards for these seven industries.
Digital HealthTech
Dieses Buch bietet einen umfassenden Einblick in die Welt von Digital HealthTech: Es vermittelt Grundlagen und Konzepte, analysiert den dynamischen Digital HealthTech-Markt sowie aktuelle und künftige Trends und Entwicklungen. Innovative Technologien und ihre praktischen Anwendungen stehen dabei im Mittelpunkt. Ebenso berücksichtigt werden ethische, regulatorische und soziale Aspekte digitaler Verantwortung. Ein Muss für alle, die sich für die Verbindung von Gesundheit und Technologie begeistern. Der Inhalt Grundlagen und Konzepte im Bereich Digital HealthTech Aktuelle und zukünftige Trends und Entwicklungen im Digital-HealthTech-Markt Konkrete technologische Modelle und deren praktische Anwendung Verantwortungsvolle Digitalisierung im Gesundheitswesen Die Herausgeber:innen Sara D’Onofrio, digitale Enthusiastin und kreative Denkerin, ist im IT-Projektmanagement mit Fokus auf Innovation tätig. Sie ist zudem Autorin und Mit-Herausgeberin der Zeitschrift HMD Praxis der Wirtschaftsinformatik bei Springer. Ehrenamtlich engagiert sie sich in der Stiftung FMsquare und als Tech-Expertin in verschiedenen (Nonprofit-)Organisationen. Christian Russ lehrt und forscht an der ZHAW zu digitalen Gesundheitsdaten, Enterprise-IT und -Governance. Sein Fokus liegt in digitalen Technologien mit Schwerpunkt auf Digital-Health-Strategien und deren Transformation im Gesundheitswesen. Er ist Vorstandsmitglied des ZHAW Digital Health Lab. Zudem wirkt er als EU-Projektgutachter, Start-up-Coach und Mentor im Bereich Tech und Digital Health. Das Kapitel "Vertrauen als Erfolgsfaktor für die Einführung von Technologien und Innovationen im Gesundheitswesen" ist unter einer Creative Commons Attribution - Non Commercial - NoDerivatives 4.0 International License über link.springer.com frei verfügbar
Performance Modeling of Computer Systems
This book addresses the gap between performance modeling theory and practice by providing a systematic approach for learning and applying performance modeling relevant principles. It covers essential hardware systems including CPUs, GPUs, accelerators, and memory systems. For each system category, a three-pronged approach is employed: teaching the theoretical background succinctly, presenting modeling methodologies and detailed microarchitectural (cycle-accurate or other) techniques, and providing hands-on implementation guidance using freely available open source simulation frameworks. Furthermore, exercises reinforce learning through combined theoretical analysis and practical implementation. This comprehensive approach offers multiple advantages. It provides thorough coverage of diverse systems, enabling professionals to build expertise without depending on specific job opportunities for learning. It allows students and new professionals to explore multiple areas before specializing with greater confidence. Finally, it serves as a practical reference for quick refreshers and skill development throughout one's career progression. What You'll Learn Master performance modeling of CPUs, GPUs, accelerators, and memory systems using top open-source tools.Refresh core computer architecture concepts essential for accurate modeling.Apply best practices to real-world scenarios and start contributing with confidence.Build hands-on skills through exercises using widely adopted simulation frameworks.Adapt modeling techniques to new hardware and emerging technologies. Who Is This Book For Beginner to Intermediate for learning and as a refresher for advanced users. Students and new professionals.
Building and Distributing Agentic AI Solutions
Discover and navigate the essential tools and technologies that streamline the product-building journey, enabling you to bring your AI solution to the Azure marketplace faster and with greater impact. This book begins with an overview of the AI and Generative AI landscape, covering the fundamentals of machine learning, data, and cost models. You will then go through market research essentials—validating ideas, analyzing competition, addressing ethical and compliance concerns, and framing pricing strategies. Further,you will delve into the practical steps of designing and building an AI-first product on Azure. Here, you will explore key design considerations such as responsible AI, domain-specific data, multi-modal interfaces, and protecting intellectual property. With hands-on insights into Azure OpenAI, Copilot Studio, and AI Foundry, the book walks through building, packaging, and operationalizing AI services. Finally, it covers the path to market—publishing on the Azure Marketplace, executing a go-to-market strategy, partnering with Microsoft, and scaling for global adoption. What You Will Learn: • The latest AI technologies from Microsoft and Open Source partners• Foundational concepts when designing agents and Knowledge Sources• Cost analysis and pricing strategies for AI products• Prototyping and integration with Microsoft Copilot Studio - the UI for AI• Deep dive into modern agentic technologies such as MCP, multi-agent collaboration, and orchestration framework patterns• Hands-on exercises with code samples and fully working concepts• Understanding Azure Marketplace requirements• Publishing to Azure Marketplace and Copilot Studio Marketplace Who This Book Is For: Project managers, software engineers, and Independent Software Vendors (ISVs)
Practical Artificial Intelligence in Julia
Develop a thorough grasp of artificial intelligence through practical implementations in Julia. This trailblazing book covers classical AI algorithms and provides practical implementations of agile AI applications, highlighting Julia's versatility and high-performance capabilities for AI development. This book takes a practical approach to ensure that readers translate theoretical concepts into tangible, real-world scenarios. Along the way, you will learn and implement neural networks, genetic algorithms, and neuroevolution from scratch. Author Dr. Alexandre Bergel uses practical examples, such as solutions to the traveling sales problem and a fun platform game (including a random level generator) to reinforce AI techniques. It also introduces Darwinian evolution principles, demonstrating how to evolve zoomorphic organisms to solve particular tasks, such as stair climbing or going over obstacles. This book stands out as among the earliest to delve into Genertic Algorithms and Neuroevolutions in Julia, and it is one of the few available that offers a comprehensive implementation of Neuroevolution. It is equally as fun as it is informative, providing readers with source code to play along with and apply to future projects. What You Will Learn: Solve simple classification tasks using neural networksUse genetic algorithms to solve complex algorithmic problemsApply Darwinian evolution principles to evolve artificially living creaturesDiscover how to Neuroevolution to build an artificial player to solve a platform game Who This Book is For: This book is written for software engineers, programmers and developers who are eager to gain practical insights into AI implementation using Julia at a beginner/intermediate level
Pro Spring Boot 4
Master enterprise-grade application and microservice development with Pro Spring Boot 4. This revised edition empowers you to fully harness the groundbreaking capabilities of Spring Boot 4, crafting robust and scalable web, cloud, and microservice solutions with unparalleled ease. Dive deep into the latest advancements, including enhanced support for Java 17 and 21, significant updates to Spring Security, refined Spring Boot Actuator metrics with Micrometer, and expanded GraalVM integration for native compilation. Explore cutting-edge features like RSocket service interfaces, enriched Spring Data JDBC flexibility, and the revolutionary AOT (Ahead-of-Time Transformation) for optimized performance. Authored by seasoned experts, including a Developer Advocate on the Spring Team at Broadcom, and a Senior Staff Engineer and Instructor at CockroachLabs, this book delivers an authoritative, pragmatic guide filled with real-world case studies of increasing complexity. Gain invaluable insights, best practices, and first-hand knowledge directly from experts shaping the future of Spring Boot technology. What You Will Learn Construct sophisticated web, cloud, microservices, and enterprise applications with the Spring Boot 4 framework.Achieve seamless persistence with JDBC, JPA, a wide array of NoSQL databases, and Distributed SQL with CockroachDB.Implement advanced messaging solutions with JMS, RabbitMQ, WebSockets, and RSocket.Leverage Spring AI to develop AI applications and agents. Connect to LLMs or other MCP Servers and utilize the appropriate tools to automate tasks.Navigate the Spring Cloud ecosystem and extend Spring Boot with custom Starters and @Enable features.Apply best practices for testing and deploying Spring Boot applications with confidence.Leverage the power of AOT (Ahead-Of-Time Transformations) and GraalVM for native compilation.Master the latest version of Spring Security for robust application protection Who This Book Is for: Experienced Spring and Java developers eager to significantly boost productivity, reduce complexity, and accelerate development cycles for their enterprise applications and software services.
Building AI Systems with Python
This book is a practical, end-to-end guide for engineers and practitioners who want to move beyond prototypes and confidently deploy machine learning and large language model solutions in real-world environments. This book guides through the entire modern machine learning lifecycle. You’ll start with foundations using NumPy, Pandas, and PyArrow for data pipelines, then build solid baselines with scikit-learn. From there, you advance into deep learning with PyTorch, transformers, and LLM adaptation techniques such as LoRA and QLoRA. You’ll explore diffusion and multimodal models, and learn to build retrieval-augmented generation systems with FAISS and pgvector. Practical chapters cover agents, tool use, evaluation frameworks, observability, and responsible AI practices including privacy, safety, and governance. Finally, you’ll master deployment techniques using FastAPI, Ray Serve, TorchServe, and cutting-edge LLM serving engines like vLLM and TGI. Each concept is paired with clear code examples, testing patterns, and operational checklists. Instead of one-off tricks, you’ll adopt repeatable workflows: schema-first tooling, reproducible training pipelines, evaluation with golden datasets, and secure production rollouts with monitoring and compliance checkpoints. In the end, this book helps you build systems that are robust, auditable, and optimized—whether you're deploying your first model or managing complex enterprise workloads. For engineers who want to ship AI confidently and responsibly, this is your practical playbook for the GenAI era. What you will learn: Implement modern AI models including transformers, diffusion, multimodal, recommenders, and RL using practical PyTorch examples. Fine tune and serve LLMs with LoRA/QLoRA, quantization, RAG, tool calling, structured prompts, and robust evaluation techniques. Design agentic AI systems with memory, planning, safe tool execution, multi agent patterns, and autonomy evaluation frameworks. Deploy and run production grade AI with MLOps/LLMOps covering serving, performance tuning, monitoring, cost control, compliance, and edge deployments. Who this book is for: This book is designed for practicing machine learning and AI engineers, software engineers moving into applied AI, data scientists building production systems, MLOps/LLMOps practitioners, and technical builders who want to go beyond demos and deploy real-world GenAI, LLM, and PyTorch-based systems at scale.
Engineering Online Experimentation and ML Evaluations
Online experimentation is now essential for modern software and machine learning teams. This book provides an engineer-first, end-to-end guide to building and operating production-ready experimentation platforms. The book begins with Part I establishing the core foundations of credible experimentation, including hypothesis testing, power analysis, sample sizing, metric design, and common pitfalls such as peeking, multiple testing, and novelty or learning effects. Part II focuses on platform engineering—traffic and identity management, mutual exclusion, event and logging design, ETL/ELT pipelines, building a stats engine with SciPy and statsmodels, SRM detection, integrating deployments with feature flags and canaries, and setting up guardrail and health monitoring. Part III presents advanced designs that improve speed and sensitivity: sequential testing with alpha spending, bootstrap intervals for ratios and quantiles, A/B/n testing with ANOVA, interleaving for ranking systems, switchback and geo experiments, and multi-armed bandits. Part IV connects experimentation to ML workflows, covering offline, shadow, canary, and A/B evaluation pipelines; Bayesian optimization for adaptive experimentation; counterfactual and IPS methods for learning from logs; and safe retraining supported by strong governance. What you will learn: Design trustworthy experiments with proper metrics, guardrails, α/power/MDE settings, and safeguards against peeking and multiple-testing errorsBuild a production-ready experimentation stack with assignment, identity/diversion, logging, ETL/ELT, a stats engine, and SRM checksRun advanced designs at scale, including sequential tests, bootstrap CIs, interleaving, switchback/geo experiments, and multi-armed banditsEvaluate ML systems from offline to online, leverage experiment logs for learning, and enable safe retraining with governance Who this book is for: The primary audience for this book includes Data Engineers, ML Engineers, and Platform or Software Architects. It is also well suited for Product and Data Scientists who want a deeper understanding of experimentation systems and the engineering principles behind them.
Advanced Rust
Master advanced features in Rust. With this book, you will learn to write robust, production-grade code by exploring powerful language capabilities essential for real-world development. Dive into the advanced language features and nuanced concepts that are typically underrepresented in mainstream Rust literature and courses. Topics include lifetime relationships, coercion, trait object safety, down casting, drop check, and more. As Rust continues to gain traction in systems programming, web services, and embedded development, mastering its advanced concepts is more important than ever. This book brings together complex Rust knowledge in a clear, accessible format, helping you build your foundational skills while navigating the language’s sometimes challenging learning curve. In the end, you’ll gain the skills and confidence to write safe, idiomatic Rust code, while enhancing your resume with advanced, career-boosting Rust expertise. What You Will Learn: Understand and implement advanced error handling strategies in RustMaster lifetime relationships, coercion rules, and trait limitations and varianceGain practical knowledge on drop check and down castingImprove code safety and readability using combinators and structured logging Who This Book is for: Intermediate to Advanced developers who have a foundational understanding of Rust and are eager to advance their skills to the next level.
Praxis der Teleportation
Dieses Buch beschreibt die Möglichkeiten der Teleportation im Metaversum. Die virtuelle Realität hier wird auf andere Spektren erweitert und der universelle Begriff „Phantomfeld“ eingeführt. Der Eintritt der Phantome ins Metaversum kann als technischer Vorgang aufgefasst werden. Displays und Headsets werden zu virtuellen Portalen. Der Einsatz von Avataren und die praktische Anwendung von VR, AR, MR oder 3D werden ausführlich behandelt. Die Grenzen der virtuellen Realität werden ausgelotet und ein Blick in die Zukunft gewagt. Können Quantencomputer die ultimative Lösung sein? Durch Markteintritt von Facebook (nun Meta) und Unreal ins Metaversum (beide mit milliardenschweren Investments) wird sich hier zweifelsfrei ein neuer Hype und Markt ergeben. Das Buch ist ein idealer Begleiter beim Eintritt ins Metaversum.
The ClojureScript Playbook
Embark on a guided tour through the Grand ClojureScript Hotel, where each “floor” presents a curated suite of interactive projects that teach you both the art and science of ClojureScript. Your journey begins in the lobby. Here, you’ll learn foundational skills like setting up a live-reloading workflow, driving Canvas animations, and handling user input. From there, you’ll move up through floors devoted to generative art, reactive UIs, data visualization, multimedia processing, 3D graphics, machine learning, and mobile apps. On every floor, you’ll work through bite-sized, hands-on demos: from a classic Pong game and fractal renderers to real-time audio wave viewers, PixiJS arcade games, and a wellness-focused “better-sleep” mobile app. Along the way, you’ll integrate popular JavaScript libraries (like Reagent, Re-frame, Nivo, Recharts, Tone.js, and Three.js) using idiomatic ClojureScript. This hands-on approach ensures you gain practical expertise in state management, interop patterns, and modern rendering pipelines. By the end of your stay, you’ll have built a diverse portfolio of projects—each fully explained step by step and you’ll know exactly how to launch your own robust ClojureScript applications on the web and mobile. Whether you’re a seasoned Clojure developer branching into browser-based interactivity, or a front-end engineer eager to explore functional programming, this book delivers the recipes, patterns, and creative spark to craft truly delightful user experiences You Will Learn To: Master REPL-driven development, tooling, and elegant namespace organization in ClojureScript.Create dynamic graphics and generative art using Canvas, Quil and Motion.js.Build state-driven interfaces with Reagent and Re-frame, and seamlessly integrate third-party widget libraries. Visualize data and multimedia with Nivo/ Recharts, Tone.js audio analyzers, and Canvas video filters.Develop 2D/3D games (PixiJS, Three.js), implement neural networks in the browser, and build mobile-native applications. This Book Is For: JavaScript Developers curious about functional programming and the ClojureScript ecosystem. Clojure Enthusiasts branching from the backend into dynamic, browser- and mobile-based inter activity. Front-End Engineers seeking a hands-on, project-centric path to mastering graphics, visualization, and games. Creative Coders looking for a robust language to build state-driven, delightful user experiences
CI/CD as a Control System
This book is your guide to a fresh approach to cloud platforms using continuous integration and continuous delivery (CI/CD) pipelines. Instead of treating DevOps and DevSecOps as a collection of tools or processes, this book teaches you to view software delivery as a control system. As you progress through the chapters, you will learn to see pipelines as execution mechanisms, understand the insights provided by feedback telemetry, create policies that define constraints, and decide how much control should be automated versus where human intervention is necessary. You will understand why delivery systems become unstable, slow, or risky as they scale, and learn how to manage these issues at the enterprise level. The book uses a practical, system‑oriented methodology. Each concept is explained using real engineering scenarios. Control‑system principles such as feedback loops, signal quality, latency, drift, and stability are directly mapped to CI/CD pipelines, observability data, security controls, and governance policies. The structure of the book takes you from foundational concepts to delivery‑system design and finally to enterprise‑scale patterns and common failure modes. The concepts in this book are not tied to specific tools or vendors. Instead, they provide a reusable mental model that applies across cloud platforms, organizations, and technologies. This perspective is especially valuable for senior engineers, architects, and leaders who design and operate delivery platforms used by multiple teams. What makes this book unique is its focus on decision‑making and control—not just automation. It shows you how to design delivery systems that remain stable while moving fast, and how to determine what should be automated, what should be constrained, and what should remain under direct human control. This makes the book relevant not only for today’s DevOps challenges but also for the future evolution of software delivery. What You Will Learn Learn how to think about software delivery as a control system, and not only as CI/CD pipelines or automation scriptsDesign DevOps and DevSecOps platforms using feedback loops, signals, and constraintsIdentify and reduce common failure patterns in modern delivery systems, such as over-control, delayed feedback, and noisy signalsApply a reusable systems-level mental model that works across different cloud providers, tools, and organizations, instead of depending on vendor-specific solutions Who This Book is For Senior DevOps engineers, DevSecOps engineers, platform engineers and cloud architects who design, build, and run CI/CD pipelines, cloud infrastructures and delivery platforms
Potenziale soziologischer Praxis
Der Sammelband zielt darauf Leistungen und Potenziale soziologischer Analysen in Theorie und Empirie anhand von Beispielen aus unterschiedlichen thematischen Zusammenhängen sichtbar zu machen.
Cybersicherheit und Desinformation
In den beiden vom Bundesministerium für Forschung, Technologie und Raumfahrt (BMFTR) geförderten Forschungsprojekten NEBULA und CrossComITS wurde Cybersicherheit insbesondere mit Fokus auf vulnerable Gruppen untersucht. Im Projekt Cross-ComITS wurde eine crossmediale Plattform für IT-Sicherheitstrainer entwickelt, die wesentliche Aspekte der Cybersicherheit speziell für vulnerable Gruppen im Sinne eines „train the trainer“-Konzepts aufarbeitet. Das Projekt NEBULA hat eine App zur automatischen Detektion von Fake News im Internet entwickelt. Der Band fasst die wesentlichen Ergebnisse auch aus der Begleitforschung dieser beiden Projekte zusammen.
ISMS für die Industrie - Der Praxisratgeber
Dieses Buch zeigt, wie Industrieunternehmen ein ISMS nach ISO/IEC 27001 aufbauen und so erweitern, dass es auch in OT-Umgebungen, unter NIS2-Anforderungen und bei KRITIS-relevanten Betriebsmodellen funktioniert. Im Mittelpunkt steht die praktische Umsetzung: Governance, Risikomanagement, Controls, IEC 62443, Incident Response, OT-SOC, Backup, Lieferkettensicherheit, Datenschutz, Betriebsrat und Reifegradmessung werden nicht nur erklärt, sondern in konkrete Dokumente, Checklisten, Rollenmodelle und Umsetzungsschritte übersetzt. Der Praxisratgeber richtet sich an CISOs, ISBs, OT-Security-Verantwortliche, Werksleitungen, Auditoren und Berater, die Informationssicherheit in industriellen Umgebungen belastbar verankern müssen. Seine Leitfrage lautet: Was verlangt die Norm – und wie sieht das in der Werkshalle tatsächlich aus? Den Zugang zum Online-Kurs finden Sie direkt im Buch.
Symbiotic Intelligence und Mensch-KI-Interaktion
Ein Framework zur Stabilisierung von Mensch-KI-Interaktion: Intelligenz als relationales Phänomen zwischen Mensch und System. Wie viel Intelligenz steckt in Künstlicher Intelligenz wirklich? Symbiotic Intelligence beschreibt ein theoretisch-operatives Framework, das Intelligenz nicht als Eigenschaft isolierter Akteure, sondern als emergentes Phänomen der Mensch-KI-Interaktion fasst. Im Zentrum stehen Resonanzschleifen und adaptive Feedbackzyklen, durch die KI als kognitiver Koprozessor wirkt und Einsichten ermöglicht, die weder Mensch noch System allein erzeugen. Gegen die These einer Verschmelzung oder Kontrolle fokussiert Thomas A. Blüm auf neue Architekturen sowie Grenzintegrität als Grundlage stabiler Langzeitinteraktion und bietet damit einen klaren Bezugsrahmen für Forschung und Lehre in Mensch-KI-Interaktion, Kognitions- und Systemtheorie.
AI-Governance im Aufsichtsrat
AI-Governance gehört als Pflichtthema auf jede Board-Agenda. Wer sie aktiv gestaltet, schafft einen echten Governance-Vorteil. Dieses Buch dient dabei als wertvoller Begleiter und Leitfaden. Es verbindet rechtliche Grundlagen wie Sorgfaltspflichten, Haftung und EU AI Act mit praxiserprobten Governance-Bausteinen von der KI-Risikoappetit-Erklärung über Ausschussstrukturen bis zum 100-Tage-Plan für das Board. Es richtet sich an Aufsichtsräte und Beiräte in börsennotierten wie auch in mittelständischen, häufig familiengeführten Unternehmen. Mit branchenspezifischen Cases, einer verständlichen Erklärung der technischen Standards und einem fundierten Ausblick auf agentische KI.
Kleines Board ganz groß - der XIAO ESP32-C3
Der Seeed Studio XIAO ESP32-C3 vereint die kompakte Bauform (nur 21 x 17,5 mm) der XIAO-Serie mit der vollen Leistung des ESP32-C3-Chips, alles inklusive integriertem Wi-Fi und Bluetooth 5.0. Dieses Buch ist ein umfassender Praxisleitfaden, um die leistungsfähige und gleichzeitig preiswerte Hardware optimal zu nutzen. Der Autor führt den Leser von den Grundlagen bis zu komplexen Projekten: Es beginnt mit Blinken und Dimmen, dann folgt ADC/PWM für präzise Sensorik und PWM-gesteuerte Lichtstimmungen – und dann werden echte, nutzbare Systeme gebaut: ▶Eine WLAN-Wetterstation mit OLED-Display und Echtzeit-Daten aus dem Netz ▶Einen Ultraschall-Parkassistenten mit akustischer Rückmeldung ▶Eine klimaüberwachende Kühlschrank-Sonde mit Deep Sleep für jahrelangen Batteriebetrieb ▶Einen Retro-Pong-Spieler mit berührungslosem Sensor ▶Eine Mikrofon-Party-App, die auf Klatschen reagiert ▶Und vieles mehr: Lichtsteuerung, Reaktionszeitmessung, Netzfrequenzanalyse, Bodenfeuchtesensoren, Stimmungs-LEDs, 7-Segment-Anzeigen…
Blockchain Foundations
Blockchain Foundations provides a rigorous, technical exploration of the cryptographic and distributed systems principles behind blockchain technology. It is written for professionals who want to understand how and why blockchains work at a mathematical and protocol level, not just how to use them. Rather than offering a high level overview, the book treats blockchain as a serious engineering discipline. Its focus is depth, precision, and long term understanding. The book begins with the Byzantine Generals Problem and progresses through hash functions, digital signatures, zero knowledge proofs, and consensus mechanisms. Each topic combines mathematical reasoning with practical code examples. This depth is essential because blockchain systems operate in adversarial environments with real economic incentives to attack flaws. True security requires more than intuition—it demands formal understanding. What distinguishes this book is its integration of cryptography, distributed systems theory, and economic game theory. Chapters build from first principles through protocol design to real world implementation concerns. Instead of teaching specific platforms, it teaches the science common to all blockchains. As the industry matures, this foundation is critical for architects who must evaluate trade offs, identify risks, and design resilient systems. What You Will Learn Core cryptographic primitives from first principles, including hash functions, digital signatures (ECDSA, Ed25519, BLS), and advanced techniques like threshold signatures and multi party computation, with security analysis and practical implementationsZero knowledge proof systems such as zk SNARKs and zk STARKs, covering mathematical foundations, polynomial commitments, and real world applications in privacy and scalabilityMajor consensus mechanisms (PoW, PoS, BFT, Avalanche, GHOST) analyzed through formal security proofs, economic incentives, and quantitative comparisons of performance, decentralization, and attack resistance Who This Book is For This book targets technical professionals who need deep foundational understanding rather than framework-specific tutorials. The primary audience includes: software engineers and blockchain protocol developers, security researchers and auditors, system architects, advanced blockchain developers, researchers in cryptography, distributed systems, or mechanism design.
IT Service Management
IT Service Management systematisch etablieren und IT-Services zukunftssicher organisieren Für IT-Leiter, IT Service Manager und IT-Berater , die IT Service Management strukturiert aufbauen oder weiterentwickeln möchtenServices bilden, Prozess-Management aufbauen und eine serviceorientierte CMDB einsetzen – praxisnah und nachvollziehbar erklärtKonkrete Hilfestellungen zur Einführung und Optimierung zentraler ITSM-Prozesse , ergänzt durch zahlreiche Praxisbeispiele und bewährte VorgehensweisenFokus auf messbare IT-Services, Governance und organisatorische Verankerung für einen nachhaltigen ServicebetriebBerücksichtigt aktuelle Entwicklungen wie die Integration von KI in das IT Service Management sowie den Einfluss agiler Methoden auf moderne IT-Organisationen Fritz Kleiner zeigt in dieser aktualisierten Neuauflage, wie Sie IT Service Management ganzheitlich und mit Unterstützung von KI in einem Unternehmen einführen und betreiben können. Anhand vieler Praxisbeispiele erfahren Sie, wie Sie IT-Dienstleistungen standardisieren, IT Service Management in der Führungsebene verankern oder Business IT Services bilden. Besonderer Schwerpunkt ist dabei u.a. das Etablieren der Prozesse des IT Service Managements wie Service Level Management, Configuration Management oder Requirement Management. Der Autor unterstützt Sie dabei, IT Service Management Schritt für Schritt im Unternehmen zu etablieren oder das bestehende IT Service Management laufend zu optimieren, sodass auch zukünftige Bedürfnisse berücksichtigt werden können. Zusätzlich wird der Einfluss von agilen Methoden im IT Service Management beleuchtet. +32 Jahre Erfahrung von ITSM inkl. Tool-Einführungen+31 Prozesse/Fähigkeiten der IT+117 Vorlagen und Vorgaben für Lieferobjekte+175 Mögliche Prinzipien für Prozesse Zielgruppe: IT-LeiterIT Service ManagerIT-DienstleistungserbringerIT-BeraterIT-FachpersonalInformatik-DozentenInformatik-Studenten
The Microsoft AI Insider's Playbook
Most books on Microsoft AI explain what the tools do. This one explains why they were built that way—and how to use that knowledge to your advantage. Krishna C. Mukherjee is a pioneering Microsoft technologist whose teams shipped the intelligent assistance features now used by hundreds of millions of people, including AutoCorrect, AutoFormat, and the spelling and grammar checkers in Microsoft Office. He architected the Intelligent Filing Manager, an AI-driven compliance system whose declarative, service-oriented design foreshadowed patterns that would later become common in SaaS platforms. He led the creation of the Bloomberg Valuation Service, applying predictive analytics to millions of financial instruments across asset classes. His career spans mainframes, personal computing, and the current era of cloud computing and AI, with a consistent focus on turning advanced capabilities into practical enterprise tools. Tracing the evolution from Microsoft’s early innovations to the intelligent enterprise, the book shows how usability, scalability, and automation shaped the modern platform. It then moves into practice: Agile delivery and efficient process design; Azure, SaaS, and strategic cloud–AI architecture; Azure AI Services; the Copilot ecosystem; and the Power Platform—all grounded in real patterns, case studies, and lessons from finance, health care, retail, and legal services. The result is a clear, experience-driven guide to building modern cloud–AI systems—connecting Microsoft’s platform decisions with the systems you are building today. What You Will Learn Architect and implement Azure AI Services (now Foundry Tools), including Azure OpenAI Service, Speech, Language, Vision, and Document Intelligence, to build enterprise-grade conversational AI and virtual assistantsApply reference patterns for data pipelines, retrieval-augmented applications, model serving, and SaaS integration, while balancing latency, reliability, quality, and costMap business processes, assess data readiness, quantify impact, and prioritize a staged roadmap from proof of concept to productionDesign cloud–AI architectures that balance performance, cost, and governance from the outsetGovern AI deployments in practice, covering security, privacy, compliance, monitoring, drift detection, incident response, and cost control Who This Book Is For Enterprise and cloud architects, Azure practitioners, and data and machine learning leaders responsible for planning or executing AI-driven digital transformation
KI in DevOps
KI in DevOps: Lösungen für echte Probleme – Code-Reviews mit KI, intelligente Alerts, automatisierte Remediation und prädiktive Kapazitätsplanung. Praktisch, ohne Marketing-Fluff. DevOps ist kaputt. Pull Requests hängen in der Review-Schleife fest, Alerts überfluten Ihr Team mit irrelevanten Meldungen, Vorfälle dauern Stunden – und die Kapazitätsplanung basiert auf Bauchgefühl. KI in DevOps ist kein weiteres Buzzword-Buch, sondern ein praktischer Leitfaden, der diese Probleme mit automatisierten, datengetriebenen Lösungen angeht. In diesem Buch lernen Sie, wie Sie: Code-Reviews mit KI beschleunigen – Parallel zu Semgrep, ohne Merges zu blockieren. Intelligente Alerts implementieren – Mit Clustering (DBSCAN), Topologie-Graphen und Root-Cause-Analysen (Claude API). Automatisierte Remediation einrichten – Mit vertrauensbasierten Entscheidungsbäumen, Runbook-YAML und RBAC-gesicherten Kubernetes-Executors. Prädiktive Kapazitätsplanung nutzen – Mit Prophet-basierten Vorhersagen und Terraform-HPA-Generatoren. Eine Referenzarchitektur aufbauen – Mit Kafka-Audit-Logs, Repo-Struktur und Kubernetes-Manifesten. Keine Theorie. Kein Marketing. Nur Code, Diagramme und Workflows, die funktionieren. Für wen? DevOps-Ingenieure, die Toil reduzieren wollen. SREs, die manuelle Vorfallsbehebung ersetzen möchten. Plattform-Teams, die selbstheilende Systeme aufbauen – ohne Vendor-Lock-in.
Agentic Predictive Intelligence
Dieses Essential zeigt, wie Vorhersagemodelle und KI Geschäftsprozesse grundlegend verändern. Agentic Predictive Intelligence verbindet prädiktive Analytik mit autonomen KI-Agenten. Anhand von Anwendungsbeispielen wird erläutert, wie Unternehmen Prognosen nutzen, um automatisierte Maßnahmen auszulösen, Workflows zu optimieren und proaktive Steuerungsprozesse aufzubauen. Gleichzeitig werden Anforderungen aufgezeigt, die für eine erfolgreiche Einführung notwendig sind. Das Werk bietet Entscheidungsträgern einen Überblick über Potenziale, Herausforderungen und Best Practices auf dem Weg zu datengetriebenen, selbstoptimierenden Unternehmensprozessen.
Governance der Kommunikationssteuerung durch Semantic Models
Dieses Essential zeigt, wie Kommunikationsverantwortliche KI-Potenziale voll nutzen, ohne Governance einzuschränken. Steuerungsmodelle werden technisch mit Daten verknüpft, so dass diese organisationsweit mit klar definierter Bedeutung nutzbar sind. Trotz moderner Infrastrukturen überwiegen oft Zweifel an Kennzahlen statt strategischer Ableitungen – bedingt durch den Verlust ihres fachlichen Entstehungskontexts. Mit der „Semantischen Steuerungsarchitektur“ bietet das Buch ein praxisnahes Modell, das Bedeutung systematisch abbildet: Ein Semantic Layer vernetzt Strategie, Zielgruppen, Themen und Wirkung. KPIs erhalten verbindliche Bedeutungsprofile – sie werden vergleich- und steuerbar.