Data Engineering In The Age Of Ai Generative Models And Deep Learning Unleashed
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DATA ENGINEERING IN THE AGE OF AI GENERATIVE MODELS AND DEEP LEARNING UNLEASHED
.The advances in data engineering technologies, including big data infrastructure, knowledge graphs, and mechanism design, will have a long-lasting impact on artificial intelligence (AI) research and development. This paper introduces data engineering in AI with a focus on the basic concepts, applications, and emerging frontiers. As a new research field, most data engineering in AI is yet to be properly defined, and there are abundant problems and applications to be explored. The primary purpose of this paper is to expose the AI community to this shining star of data science, stimulate AI researchers to think differently and form a roadmap of data engineering for AI. Since this is primarily an informal essay rather than an academic paper, its coverage is limited. The vast majority of the stimulating studies and ongoing projects are not mentioned in the paper.
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.
Artificial Intelligence Applications for Sustainable Construction
Artificial Intelligence Applications for Sustainable Construction presents the latest developments in AI and ML technologies applied to real-world civil engineering concerns. With an increasing amount of attention on the environmental impact of every industry, more construction projects are going to require sustainable construction practices. This volume offers research evidence, simulation results, and case studies to support this change. Sustainable construction, in fact, not only uses renewable and recyclable materials when building new structures or repairing deteriorating ones, but also adopts all possible methods to reduce energy consumption and waste.The concisely written but comprehensive, practical knowledge put forward by this international group of highly specialized editors and contributors will prove to be beneficial to engineering students and professionals alike. - Presents convincing "success stories that encourage application of AI-powered tools to civil engineering - Provides a wealth of valuable technical information to address and resolve many challenging construction problems - Illustrates the most recent shifts in thinking and practice for sustainable construction