Ai Augmented Engineer
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AI-Augmented Engineer
🚀 Unlock Your Full Engineering Potential with AI — Before It Replaces You What if you could design faster, make smarter decisions, and innovate with confidence — not by replacing your expertise, but by amplifying it with artificial intelligence? In AI-Augmented Engineer , you’ll discover how to harness the power of AI without needing a data science degree . From optimizing complex systems to automating repetitive tasks and predicting failures before they happen, this book gives you the tools and strategies to stay ahead in a world that’s changing faster than ever. ✅ Stop struggling with outdated workflows ✅ Start innovating with intelligent efficiency ✅ Future-proof your career with real-world AI skills Whether you’re in civil, mechanical, electrical, or structural engineering, this book is your roadmap to working smarter, not harder — and leading the next wave of innovation. Don’t get left behind. Become the engineer of tomorrow — today.
Generative AI in Software Engineering
Author: Aguilar-Calderón, José Alfonso
language: en
Publisher: IGI Global
Release Date: 2025-06-13
Generative AI transforms the landscape of software engineering, enabling automation, creativity, and efficiency throughout development. By leveraging advanced machine learning models, like large language models and code generation tools, developers can automate code generation, streamline testing, and design software architectures. This shift accelerates development timelines and redefines the roles of engineers and the skills required in modern software teams. As generative AI evolves, its integration into software engineering raises important questions around reliability, security, and human-AI collaboration. Generative AI in Software Engineering explores the evolving role of generative AI in the software engineering landscape. It examines how AI accelerates software development, reduces costs, and enhances creativity, offering real-world benefits for businesses. This book covers topics such as quantum computing, visual intelligence, and environment science, and is a useful resource for business owners, computer engineers, academicians, researchers, and data scientists.
Systems Engineering and Artificial Intelligence
Author: William F. Lawless
language: en
Publisher: Springer Nature
Release Date: 2021-11-02
This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams—where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges.