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The goal of this book is to help enterprises understand what makes LLMs so groundbreaking compared to previous solutions and how they can benefit from adopting or developing them. It also aims to help enterprises get a head start by outlining the most crucial steps to LLM development, training, and deployment. To achieve these goals, the book is divided into three parts:
Part 1 defines LLMs and outlines the technological and methodological advancements over the years that made them possible. It also tackles more practical topics, such as how enterprises can develop their own LLMs and the most notable companies in the LLM field, to help enterprises understand how adopting LLMs can unlock cutting-edge possibilities and revolutionize their operations.
Part 2 discusses five major use cases of LLMs within enterprises, including content generation, summarization, and chatbot support. Each use case is exemplified with real-life apps and case studies, to show how LLMs can solve real problems and help enterprises achieve specific objectives.
Part 3 is a practical guide for enterprises that want to build, train, and deploy their own LLMs. It provides an overview of necessary pre-requirements and possible trade-offs with different development and deployment methods. ML engineers and data scientists can use this as a reference throughout their LLM development processes.
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