The integration of Large Language Models (LLMs) into enterprise applications marks a significant advancement in how businesses leverage AI for enhanced decision-making and operational efficiency. This book is an essential guide for professionals seeking to integrate LLMs within their enterprise applications. LLMs in Enterprise not only demystifies the complexity behind LLM deployment but also provides a structured approach to enhancing decision-making and operational efficiency with AI.

Starting with an introduction to the foundational concepts of LLMs, the book swiftly moves to practical applications, emphasizing real-world challenges and solutions. It covers a range of topics from data strategies. We explore various design patterns that are particularly effective in optimizing and deploying LLMs in enterprise environments. From fine-tuning strategies to advanced inferencing patterns, the book provides a toolkit for harnessing the power of LLMs to solve complex challenges and drive innovation in business processes.

By the end of this book, you will have a deep understanding of various design patterns for LLMs and how to implement these patterns to enhance the performance and scalability of their Generative AI solutions.

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Spis treści

LLMs in Enterprise. Design strategies for large language model development, design patterns and best practices eBook -- spis treści

• 1. Introduction to Large Language Models (LLMs)
• 2. LLMs in Enterprise: Applications, Challenges, and Design Patterns
• 3. Data and Training in Foundation Models
• 4. Fine-Tuning and Retrieval-Augmented Generation (RAG) Patterns
• 5. Customizing Contextual LLMs Patterns
• 6. Evaluation Patterns
• 7. Data Strategy for LLMs
• 8. Model Deployment
• 9. Accelerated and Optimized Inferencing Patterns
• 10. LLMs in Production
• 11. RAG 2.0: Beyond Mainstream RAG
• 12. Connected LLMs Pattern
• 13. Responsible AI in LLMs
• 14. Emerging Trends and Multimodality