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Revolution of AI and Machine Learning
for Design and Automation

Revolution of AI and Machine Learning for Design and Automation

Routledge Studies in Central and Eastern European Business and Economics

This book examines how emerging digital technologies are reshaping industrial production and national energy infrastructures. It is intended for researchers and postgraduate students seeking to understand or implement effective digital strategies in industry and the energy sector.

Energy Systems, Manufacturing, and Sustainability

The Digital Transformation of Production and Operations Management

Routledge Studies in Innovation, Organizations and Technology

Psychological and Social Implications

Artificial Intelligence in Creative Industries

This lively and fascinating text traces the key developments in computation – from 3000 B.C. to the present day – in an easy-to-follow and concise manner.
The book embarks upon a journey from ancient Egypt to modern times-- taking in mechanical calculators, early digital computers, to software engineering, to the first personal computers and mobile phones, and the invention of the World Wide Web, among other topics. This expanded and revised 4th edition examines legal and ethical issues that arise in the computing field, as well as innovations such as quantum computing and Bitcoin.
 
Topics and features:

<li>Offers many pedagogical features such as chapter-opening key topics, chapter introductions and summaries, exercises, and a glossary

</li><li>Discusses major figures such as Boole, Babbage, Shannon, Turing, and Von Neumann

</li><li>Reviews early computers developed in the United States, Germany and Britain

</li><li>Explores the development of the IBM 360 and the birth of the software industry

</li><li>Reviews the history of software engineering, programming languages, and operating systems, and examines ethical software engineering

</li><li>Investigates progress of the field of artificial intelligence, including ethical AI

</li><li>Reviews the introduction of the personal computer, the World Wide Web, mobile phone technology, and ethical social media

</li><li>Discusses innovations such as Bitcoin, quantum computing and nanotechnology

</li><li>Examines legal and ethical aspects of computing, computer crime and cybersecurity



 
This clearly written and broad-ranging text gives the reader a flavour of the history and stimulates further study in the subject. As such, it will be of benefit to students of computer science, while also capturing the interest of the more casual reader.
Dr. Gerard O'Regan is an independent researcher and visiting professor with research interests in software quality and software process improvement, mathematical approaches to software quality, and the history of computing. He is the author of several Springer books including Concise Guide to Software Engineering, Mathematical Foundations of Software Engineering, and Ethical and Legal Aspects of Computing.
</li>

A Brief History of Computing

Studieren, aber richtig

Künstliche Intelligenz sinnvoll in den wissenschaftlichen Schreibprozess zu integrieren, ohne dabei die Verantwortung für den eigenen Text abzugeben – wie das gelingt, zeigt Isabella Buck in ihrem Buch. 
Sie erklärt Begrifflichkeiten und Funktionsweisen und geht auf Herausforderungen bei der Anwendung, wie ethische und datenschutzrechtliche Aspekte, ein. Anschließend erläutert sie verschiedene Nutzungsmöglichkeiten von generativer KI beim wissenschaftlichen Schreiben und zeigt, wie Prompting gelingen kann. In der zweiten Auflage hat sie neueste wissenschaftliche Studien integriert und das Kapitel über Prompting um einen Abschnitt zum Context Engineering ergänzt.
Ein aufschlussreiches Buch für Studierende mit erster Erfahrung im wissenschaftlichen Schreiben und Promovierende aller Fachrichtungen.

Wissenschaftliches Schreiben mit KI

A new era of SQL Server is here, and this latest edition of Grant Fritchey’s best-selling dive into SQL Server query performance can ensure your queries keep up.

The fundamentals are still here: You’ll learn how statistics and indexes impact performance, how to identify poorly performing queries, and how to discover effective solutions. But this new edition also includes advanced features unique to SQL Server 2025, such as AI integration for automatic tuning, insights on using extended events, automatic execution plan correction, and more. It’s a must-have resource designed to empower you to troubleshoot slow-performing queries and make them run faster than ever.

The book is a treasure trove of instruction, insight, and advice. As you dive in, you’ll encounter key fundamentals, from statistics and data distribution to cardinality and parameter sniffing, and learn to analyze and design your indexes and queries using best practices that prevent performance problems before they occur. You’ll also explore advanced features like Query Store for managing and controlling execution plans, automated performance tuning, and memory-optimized OLTP tables and procedures—and learn how SQL Server 2025 makes it all more powerful and automatable than ever.

What You Will Learn

Use Query Store to understand and easily change query performance

Recognize and eliminate bottlenecks leading to slow performance

Tune queries whether on-premises, in containers, or on cloud platform providers

Implement best practices in T-SQL to minimize performance risk

Design in the performance that you need through careful query and index design

Understand how built-in, automatic tuning can assist your performance enhancement efforts

Protect query performance during upgrades to the newer versions of SQL Server




Who This Book Is For

Developers and database administrators with responsibility for query performance in SQL Server environments, and anyone responsible for writing or creating T-SQL queries and in need of insight into bottlenecks—including how to identify them, understand them, and eliminate them

Troubleshoot and Optimize Query Performance

SQL Server 2025 Query Performance Tuning

B2B marketers face unique challenges, including non-linear buyer journeys, multiple decision-makers, and long sales cycles, alongside the (mis)perception of their work being boring and lacking in creativity. Written by a seasoned industry practitioner, The Future of B2B Marketing: Harnessing AI to Unlock Smarter Decisions offers original insights and guidance into the evolving B2B landscape, showing how artificial intelligence can be applied at every stage of the buying journey - from capturing awareness from the right audience and generating quality engagement through to optimizing measurement and performance. It serves to both guide experienced professionals while also supporting those new to the industry, offering reminders, confidence-building, and practical approaches for navigating the everyday complexities of B2B marketing. Combining research, frameworks, case studies, and career-focused advice, this book helps marketers embrace new technologies and learn how to put AI into practice, using their own judgement and expertise to act effectively - and ultimately make smarter decisions.

Harnessing AI to unlock smarter decisions

The Future of B2B Marketing

This book responds to the need to distinguish human creations from those produced by AI. It does so by tracing human attributes of authorship and inventorship in statutory requirements for protection and ownership in European copyright and patent laws. Its main contribution lies in exposing shortcomings in how the laws are applied in the UK, Germany, and France. It shows that the human origin of creations is traditionally inferred from their expressive form or technical character. Given the advancements in AI, such inferences are no longer legitimate. What is more, these shortcomings may eventually lead to granting copyright or patent protection where none is lawfully permitted or sufficiently justified. To remedy the situation, this book offers doctrinal and conceptual amendments and proposes law reforms to implement them. This book guides authorities, practitioners, and students through the main arguments of the debate concerning copyright and patents for objects entirely or partly generated by AI. It also makes original contributions to advance the ongoing academic and policy debates on AI and intellectual property law.

Authorship and Inventorship Revisited

Copyright and Patent Laws for the Age of Artificial Intelligence

Cut through the hype. Master the basics. Transform your work

How to AI

edition suhrkamp

Was kommt danach?

Liberale Demokratie ohne Zukunft

A sharp history of journalism's digital unraveling in the age of algorithms. In the past three decades, the battle between big tech and big journalism has reshaped how we consume the news. Jason Whittaker delves into how tech giants outmaneuvered traditional media companies, siphoning off advertising revenue and audience attention. As journalism struggled to adapt, social media platforms evolved from utopian public spaces into breeding grounds for misinformation and fake news, eroding public trust. The influence of billionaires further complicated the digital ecosystem, swaying public opinion and exercising direct political power, of which previous media moguls could only dream. More recently, AI has begun to revolutionize content creation, distribution, and consumption. Overall, this thirty-year period has witnessed a tangled mix of progress, contention, and disinformation. Incorporating stories about The Washington Post, The New York Times, The Atlantic, The Los Angeles Times, Bloomberg, and many other media outlets from around the world, and discussing key figures and companies in big tech and AI like Facebook/Meta, Cambridge Analytica, Google, Microsoft, Twitter/X and Elon Musk, Edward Snowden, Jakob Uszkoreit, OpenAI, ChatGPT, DeepSeek, and more, Whittaker provides an incisive examination of the frequently combative relations of these two industries and the uncertain future of the news in the digital age.

Big Tech v. Big Journalism

You Want What We've Got

A critical introduction to the psychiatric technologies of the future Artificial intelligence (AI) promises to transform nearly every area of modern life, and psychiatry is no exception. The field faces the mounting crisises in diagnostic inaccuracy, treatment stagnation, and persistent failures in suicide prevention, while traditional approaches struggle to keep pace with patient needs. AI and neuroscience offer a new path forward, pointing toward a future where mental health care is grounded in objective data, individualized predictions, and biologically informed treatments. Decoding Despair provides a cutting-edge look at these emerging scientific possibilities and the long-standing norms they may replace. Beginning with an examination of psychiatry's current challenges, it moves toward a present where AI-powered tools are beginning to reshape diagnostics, treatment selection, and drug development. The book offers readers a deeper understanding of mental health as both a scientific field and a lived human experience, while igniting an essential conversation about the transformative potential of precision psychiatry and technology. Decoding Despair readers will also find: <ul> <li>Exploration of the patient's journey from first symptoms to being prescribed medication</li> <li>Deep dive into the healthcare system and an understanding of the connections between stakeholders</li> <li>Clear explanations of how AI models work and how they can be practically applied to solving issues in mental health</li> <li>Deep introduction into the world of data and the different models of data acquisition necessary for building AI solutions</li> <li>Analysis of the potential innovations that could come first and the conditions necessary for them to occur</li> </ul> &nbsp; Decoding Despair is ideal for professionals and innovators building the future of psychiatry-as well as anyone seeking to understand their own mental health and the technological breakthroughs poised to reshape this critical field of care.

How AI is Reshaping Psychiatry

Decoding Despair

Predictable Ops is a practical leadership framework for IT operations leaders and their business partners navigating the complexities of AI-driven transformation. The book delivers eight clear rules grouped into two tracks: Operational Trust and Preparation &amp; Foresight. This system helps leaders build reliable, cost-aware, resilient services — and lead decisively when machine-driven insights must be balanced with human judgment.

Each rule includes real-world anecdotes — from cloud migrations and vendor licensing negotiations to critical incident communications and team accountability gaps. Predictable Ops makes the system repeatable through reflection questions, templates, and ‘Try It This Week’ actions.

Where other books focus narrowly on DevOps, SRE, or AI strategy, Predictable Ops bridges the daily realities of operations leaders who must stabilize services while explaining the risks and value of AI to partners who depend on them.

With trust, clear forecasting, transparent communication, and decisive leadership, Predictable Ops shows readers how to deliver services that stay stable, boring, and trusted — so that AI and future platforms multiply value instead of chaos.

Leading IT in the Age of AI

Predictable Ops

Revolution of AI and Machine Learning for Design and Automation

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