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Large Language Models An Introduction (eBook)

Understanding the Fundamentals and Applications of Generative AI
eBook Download: EPUB
2024
503 Seiten
Packt Publishing (Verlag)
978-1-83664-736-2 (ISBN)

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Large Language Models  An Introduction -  Oswald Campesato,  Mercury Learning and Information
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This book provides a comprehensive overview of large language models (LLMs) and generative AI, covering foundational principles, advanced concepts, and practical applications. It begins with an introduction to the generative AI landscape, examining key features, popular techniques, and its influence on industries like art, business, and technology. The book also explores prominent models like ChatGPT and GPT-4, detailing their architectures, capabilities, and applications in text generation, code assistance, and conversational AI.
Additionally, the book traces the evolution of LLMs, particularly focusing on the BERT family and its wide-ranging applications in natural language processing, translation, and multilingual tasks. Readers will also gain expertise in prompt engineering, learning practical tips and examples to interact more effectively with LLMs.
In later chapters, the book tackles advanced topics such as fine-tuning LLMs, working with SVG, and concepts like few-shot learning and reinforcement learning. It concludes with discussions on ethical issues, biases in generative AI, and emerging trends like AI's integration with IoT, quantum computing, and neuromorphic computing. This guide equips professionals and enthusiasts with a thorough understanding of generative AI's present and future.


Explore the world of large language models and generative AI, from foundational concepts to advanced applications. This book covers key topics, technologies, and real-world use cases, making it a must-read for AI enthusiasts and professionals.Key FeaturesComprehensive coverage of generative AI and large language models (LLMs).Detailed examination of prompt engineering and fine-tuning techniques.Insights into the impact of AI on society and ethical considerations.Book DescriptionThis book provides a comprehensive overview of large language models (LLMs) and generative AI, covering foundational principles, advanced concepts, and practical applications. It begins with an introduction to the generative AI landscape, examining key features, popular techniques, and its influence on industries like art, business, and technology. The book also explores prominent models like ChatGPT and GPT-4, detailing their architectures, capabilities, and applications in text generation, code assistance, and conversational AI. Additionally, the book traces the evolution of LLMs, particularly focusing on the BERT family and its wide-ranging applications in natural language processing, translation, and multilingual tasks. Readers will also gain expertise in prompt engineering, learning practical tips and examples to interact more effectively with LLMs. In later chapters, the book tackles advanced topics such as fine-tuning LLMs, working with SVG, and concepts like few-shot learning and reinforcement learning. It concludes with discussions on ethical issues, biases in generative AI, and emerging trends like AI s integration with IoT, quantum computing, and neuromorphic computing. This guide equips professionals and enthusiasts with a thorough understanding of generative AI's present and future.What you will learnExplore the basics of generative AI.Learn about ChatGPT and GPT-4, including their uses.Understand techniques for prompt engineering.Navigate the architectures and training processes of large language models (LLMs).Examine various fine-tuning methods.Discover the impact of AI on employment and job roles.Who this book is forThe ideal audience includes AI enthusiasts, data scientists, machine learning practitioners, and technology professionals looking to deepen their understanding of generative AI and LLMs. Readers should have a foundational knowledge of AI and machine learning concepts. ]]>
Erscheint lt. Verlag 7.10.2024
Sprache englisch
Themenwelt Informatik Theorie / Studium Algorithmen
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
ISBN-10 1-83664-736-0 / 1836647360
ISBN-13 978-1-83664-736-2 / 9781836647362
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