ChatGPT: Principles and Architecture is an important comprehensive book, bringing readers up to date with the latest developments in large language models such as ChatGPT, and fulfilling the need for a resource that not only explains the theory but also provides insights into the implementation of AI technologies. The book bridges the knowledge gap between theoretical AI concepts and their practical applications. It equips industry professionals and researchers with a deeper understanding of large language models, enabling them to leverage these technologies effectively in their respective fields. This book tackles the complexity of understanding large language models and their practical applications. It demystifies the underlying technologies and strategies used in developing ChatGPT and similar models, offering readers a clear roadmap from conceptual understanding to practical implementation. By combining theoretical knowledge with real-world examples, the book enables readers to grasp the nuances of AI technologies, paving the way for innovative applications and solutions in their professional domains. In exploring the intricacies of large language models, the book focuses on the principles, architecture, pretraining, transfer learning, and middleware programming techniques of ChatGPT, providing a useful resource for the research and academic communities. The book addresses the needs of industry professionals, researchers and students in the field of AI and computer science who face daily challenges in understanding and implementing complex large language model technologies. It provides them with the necessary theoretical knowledge and practical insights to effectively apply these technologies in their work. Furthermore, it helps in overcoming the gap between theoretical concepts of large language models and their practical applications, offering guidance on how to navigate through the rapidly evolving landscape of AI.
