Название: AI in Material Science: Revolutionizing Construction in the Age of Industry 4.0
Автор: Sуеd Sааd, Sуеd Аmmаd, Кumееl Rаshееd
Издательство: CRC Press
Год: 2025
Страниц: 289
Язык: английский
Формат: pdf (true)
Размер: 11.7 MB

This book explores the transformative impact of Artificial Intelligence (AI) on material science and construction practices in the Industry 4.0 landscape. It enquires into AI history and applications, examining material optimization, smart materials, and AI in construction. Covering automation, robotics, and AI-assisted design, the book provides insights into ethical considerations and future trends. A modern reference for scholars and professionals, it bridges academia and practical applications in the dynamic intersection of AI and materials science. As an academic exploration, this book navigates the ever-evolving landscape of Artificial Intelligence’s (AI) influence on modern materials within the Industry 4.0 era. The comprehensive nature of this work is rooted in the foundational principles and realistic applications of AI, focusing on its integration into material science and construction practices. Our collective goal in crafting this collection stems from a recognition of the widening breach between academic literature and industry-centric publications within the AI and materials science domain. AI has become an industry-wide revolutionary force in the context of Industry 4.0. The book presents a solid case for continuing the investigation of AI in the field of material science through this academic and professional introduction, opening the door for readers to learn about the revolutionary possibilities that lie at the intersection of AI and the construction industry. Learning about Artificial Intelligence, the fundamental concepts and tenets of AI are covered in this section. It examines the idea of AI, the distinctions between specific and general AI, and the many methods and algorithms used in systems that use AI. Readers can comprehend AI’s possible uses and consequences in the setting of material science by developing a solid comprehension of the technology. AI represents one of the most transformative and interesting fields in ultramodern technology and computer wisdom.

Название: Intelligent Technologies for Automated Electronic Systems
Автор: S. Каnnаdhаsаn, R. Nаgаrаjаn, N. Shаnmugаsundаrаm, Jуоtir Моу Сhаttеrjее
Издательство: Bentham Books
Год: 2024
Страниц: 234
Язык: английский
Формат: pdf (true)
Размер: 48.4 MB

This volume explores a diverse range of applications for automated Machine Learning and predictive analytics. The content provides use cases for Machine Learning in different industries such as healthcare, agriculture, cybersecurity, computing and transportation. The major objective of Smart Electronic Systems is to provide a platform where researchers from the fields of hardware and software may work together under one roof to speed up the development of smart electronic systems. Effective and secure data sensing, storage, and processing are essential in today's information age. Modern smart electronic systems meet the criteria of effective sensing, storage, and processing. Effective techniques and software that allow for a quicker analysis and retrieval of necessary data are simultaneously becoming more important. The internet world now includes big data, which comprises large, complex data collections. It is becoming harder to store and analyse the vast amount of structured and unstructured data that has to be collected. With concurrent hardware and software development, the Internet of Things (IoT) and cyber-physical systems (CPS) have been growing to include everyday consumer electronics. The effectiveness and performance of current and next generations of computing and information processing systems depend on advancements in both hardware and software. Some of the focused areas in this field include memristor and memristive systems, advanced 3D IC technologies, design methodologies, and 3D pacing. Others include molecular electronics, biosensors, bio-molecular and biologically inspired computing, nanoelectronics for energy harvesting, spintronics, domain-wall and phase-change memories, and nanoelectronics for energy harvesting.

Название: Generative AI in Action (MEAP v5)
Автор: Аmit Ваhrее
Издательство: Manning Publications
Год: 2024
Страниц: 266
Язык: английский
Формат: epub
Размер: 39.7 MB

Generative AI can transform your business by streamlining the process of creating text, images, and code. This book will show you how to get in on the action! Generative AI has created new opportunities for organizations of all sizes. You can easily use tools like ChatGPT, Bard, and Stable Diffusion to generate text and images for product catalogs, marketing campaigns, technical reporting, and other common tasks. Coding assistants like Copilot are accelerating productivity in software teams. In this insightful book, author Amit Bahree shares his experience leading Generative AI projects at Microsoft for nearly a decade, starting well before the current GPT revolution. Generative AI in Action shows you exactly how to add generative AI tools for text, images, and code, and more into your organization’s strategies and projects. The book begins with the fundamentals of generative AI models and architectures, and introduces practical use-cases to create efficient processes for marketing, software development, business report generation and other practical tasks. You’ll quickly master best practices for prompt engineering, model fine tuning and evaluation, and explore the emerging architecture patterns that support generative AI in your enterprise workflow. Along the way, you’ll explore important facts about AI safety and ethics, and look ahead to new trends such as explainable AI, transfer learning, and reinforcement learning. With a frank discussion of risks like hallucinations and jailbreaks, Generative AI in Action gives you the insight you need to incorporate these powerful technologies with confidence. For enterprise architects and senior developers interested in upgrading their architectures with generative AI.

Название: Deep Learning Models: A Practical Approach for Hands-On Professionals
Автор: Jоnаh Gаmbа
Издательство: Springer
Год: 2024
Страниц: 211
Язык: английский
Формат: pdf (true), epub
Размер: 65.3 MB

This book focuses on and prioritizes a practical approach, minimizing theoretical concepts to deliver algorithms effectively. With Deep Learning emerging as a vibrant field of research and development in numerous industrial applications, there is a pressing need for accessible resources that provide comprehensive examples and quick guidance. Unfortunately, many existing books on the market tend to emphasize theoretical aspects, leaving newcomers scrambling for practical guidance. This book takes a different approach by focusing on practicality while keeping theoretical concepts to a necessary minimum. The book begins by laying a foundation of basic information on Deep Learning, gradually delving into the subject matter to explain and illustrate the limitations of existing algorithms. A dedicated chapter is allocated to evaluating the performance of multiple algorithms on specific datasets, highlighting techniques and strategies that can address real-world challenges when Deep Learning is employed. The Chapter 2 introduce some of the concepts needed to start building Deep Learning models in Python. The chapter starts with basic principles related to data manipulation and ends with explanation on how to set up the modelling environment. It is expected that the reader is familiar with some high-level programming concepts which are very easy to acquire within a short space of time. Deep Learning models mostly deal with vectors and matrices as we know them from linear algebra. This book is designed to equip professionals with the necessary skills to thrive in the active field of Deep Learning, where it has the potential to revolutionize traditional problem-solving approaches.

Название: Generative Analysis: The Power of Generative AI for Object-Oriented Software Engineering with UML (Early Release)
Автор: Jim Аrlоw, Ilа Nеustаdt
Издательство: Addison-Wesley Professional/Pearson Education
Год: 2024
Страниц: 512
Язык: английский
Формат: epub (true)
Размер: 67.4 MB

Learn a new method of object-oriented analysis called generative analysis and keep your skill-set on pace with how generative AI is transforming the face of software engineering. Generative AI is revolutionizing many industries, including software engineering. Many aspects of manual coding are becoming automated, and the skills needed by software engineers, developers, and analysts are evolving. Anyone who writes or works with code will need to produce precise analysis artifacts to feed the AI code generation process. Enter generative analysis: a precise, structured way to for software engineers, programmers, and analysts to transition to this new, AI-enhanced, software engineering world. In Generative Analysis, experts Jim Arlow and Ila Neustadt leverage literate modeling, M++, and multivalent logic to lay out a precise and structured, step-by-step approach to object-oriented analysis that produces clear and unambiguous results suitable for further processing into code by generative AI systems such as Copilot, ChatGPT, and Gemini. Ideally, you would be a business analyst who is also a competent programmer who is comfortable building models of software systems with the Unified Modeling Language (UML). We understand that this is a very big ask! However, you don’t need to be an expert programmer, you just need to be able to read code and understand UML artefacts without necessarily understanding the fine details. For code examples, we have chosen Python because this is probably the most easily readable programming language.

Название: Innovation in the University 4.0 System based on Smart Technologies
Автор: Shаshi Каnt Guрtа, Jоаnnа Rоsаk-Szуrосkа
Издательство: CRC Press
Год: 2024
Страниц: 241
Язык: английский
Формат: pdf (true)
Размер: 36.2 MB

This text presents a comprehensive analysis of mathematical formulations for proving the effectiveness of Artificial Intelligence in education and investigates the possibilities for integrating advanced Artificial Intelligence algorithms. Artificial Intelligence (AI) in education signifies a paradigm shift in teaching and learning. A major driving force behind AI is the concept of neural networks and Deep Learning. These powerful tools enable AI applications to deliver personalized, dynamic, and engaging learning experiences. To understand the role of these technologies in education, we must first comprehend the basics. Neural networks are AI systems modeled after the human brain, consisting of interconnected layers of nodes, or “neurons,” that process information. These layers constitute an input layer, one or more hidden layers, and an output layer. Each node processes the input it receives and passes on the result, simulating the process of human brain cells transmitting signals. Deep Learning, a subset of Machine Learning, involves using neural networks with multiple hidden layers. The text is primarily written for graduate students, postgraduate students, and academic researchers working in the fields of Computer Science and engineering, information technology and Machine Learning.

Название: Intelligent Systems and Sustainable Computational Models: Concepts, Architecture, and Practical Applications
Автор: Rаjgаnеsh Nаgаrаjаn, Sеnthil Кumаr Nаrауаnаsаmу
Издательство: CRC Press
Год: 2024
Страниц: 429
Язык: английский
Формат: pdf (true)
Размер: 20.0 MB

The fields of intelligent systems and sustainability have been gaining momentum in the research community. They have drawn interest in such research fields as Computer Science, information technology, electrical engineering, and other associated engineering disciples. The promise of intelligent systems applied to sustainability is becoming a reality due to the recent advancements in the Internet of Things (IoT), Artificial Intelligence (AI), Big Data, Blockchain, Deep Learning, and Machine Learning. The emergence of intelligent systems has given rise to a wide range of techniques and algorithms using an ensemble approach to implement novel solutions for complex problems associated with sustainability. Intelligent Systems and Sustainable Computational Models: Concepts, Architecture, and Practical Applications explores this ensemble approach towards building a sustainable future. The book helps researchers to apply intelligent systems to computational sustainability models to propose efficient methods, techniques, and tools.

Название: Cognitive Analytics and Reinforcement Learning: Theories, Techniques and Applications
Автор: Еlkkiуа R., Subrаmаniуаswаmу V.
Издательство: Wiley-Scrivener
Год: 2024
Страниц: 384
Язык: английский
Формат: epub
Размер: 10.1 MB

The combination of cognitive analytics and Reinforcement Learning is a transformational force in the field of modern technological breakthroughs, reshaping the decision-making, problem-solving, and innovation landscape; this book offers an examination of the profound overlap between these two fields and illuminates its significant consequences for business, academia, and research. Cognitive analytics and Reinforcement Learning are pivotal branches of Artificial Intelligence. They have garnered increased attention in the research field and industry domain on how humans perceive, interpret, and respond to information. Cognitive science allows us to understand data, mimic human cognitive processes, and make informed decisions to identify patterns and adapt to dynamic situations. The process enhances the capabilities of various applications. Readers will uncover the latest advancements in AI and Machine Learning, gaining valuable insights into how these technologies are revolutionizing various industries, including transforming healthcare by enabling smarter diagnosis and treatment decisions, enhancing the efficiency of smart cities through dynamic decision control, optimizing debt collection strategies, predicting optimal moves in complex scenarios like chess, and much more. The book caters to a diverse audience that spans academic researchers, AI practitioners, data scientists, industry leaders, tech enthusiasts, and educators who associate with Artificial Intelligence, data analytics, and cognitive sciences.

Название: Mastering Large Language Models: Advanced techniques, applications, cutting-edge methods, and top LLMs
Автор: Sаnkеt Subhаsh Кhаndаrе
Издательство: BPB Publications
Год: 2024
Страниц: 903
Язык: английский
Формат: pdf, epub
Размер: 13.2 MB

Do not just talk AI, build it: Your guide to LLM application development. Transform your business landscape with the formidable prowess of large language models (LLMs). The book provides you with practical insights, guiding you through conceiving, designing, and implementing impactful LLM-driven applications. This book explores NLP fundamentals like applications, evolution, components and language models. It teaches data pre-processing, neural networks, and specific architectures like RNNs, CNNs, and transformers. It tackles training challenges, advanced techniques such as GANs, meta-learning, and introduces top LLM models like GPT-3 and BERT. It also covers prompt engineering. Finally, it showcases LLM applications and emphasizes responsible development and deployment. With this book as your compass, you will navigate the ever-evolving landscape of LLM technology, staying ahead of the curve with the latest advancements and industry best practices. This book is tailored for those aiming to master large language models, including seasoned researchers, data scientists, developers, and practitioners in natural language processing (NLP).

Название: GPT-3. Руководство по использованию API Open AI
Автор: Caндpa Kyблик, Шyбxaм Caбy
Издательство: ДМК Пресс
Год: 2023
Страниц: 174
Язык: русский
Формат: pdf
Размер: 10.3 MB

В книге исследуется мощная языковая модель GPT-3, упрощающая создание приложений с искусственным интеллектом. Первая часть посвящена основам API OpenAI, во второй описывается динамичная и процветающая среда, возникшая вокруг GPT-3. Представлены рекомендации по использованию GPT-3 для создания новых бизнес-продуктов. Обсуждается влияние GPT-3 на развитие мировой экономики и такие передовые тенденции, как программирование без кода и достижение общего искусственного интеллекта. Книга рассчитана на читателей, интересующихся современными технологиями. Она будет особенно полезна предпринимателям, деятельность которых связана с индустрией искусственного интеллекта, а также тем, кто планирует использовать языковые способности GPT-3 для реализации творческих проектов. Первая часть книги посвящена основам API OpenAI. Во второй части книги мы исследуем пеструю экосистему, органично и стремительно возникшую вокруг GPT-3. В главе 1 изложен контекст и основные определения, необходимые для комфортного изучения дальнейших тем. В главе 2 мы глубоко погружаемся в API, разбивая его на наиболее важные элементы, такие как базовые модели и конечные точки, описывая их назначение и способы использования для читателей, которые хотят взаимодействовать с ними на более глубоком уровне. Глава 3 содержит простой и интересный рецепт для вашего первого приложения на базе GPT-3.