Guide to Deploying Production-Quality GenAI Applications

This guide outlines the process of deploying production-quality Generative AI (GenAI) applications. It begins by emphasizing the importance of evolving data infrastructure to support GenAI-powered applications, highlighting the role of data lakehouses in achieving this goal. The document details the stages involved in deploying GenAI, starting from foundational models to advanced techniques such as prompt engineering and retrieval augmented generation (RAG). Each stage includes use cases that illustrate practical applications of GenAI, such as automated analysis of product reviews and creating bespoke large language models (LLMs). The guide also discusses the significance of data quality and the tools necessary for developers to evaluate and optimize their GenAI applications. Furthermore, it presents insights into training models effectively and the challenges associated with fine-tuning and evaluating LLMs. Overall, the document serves as a comprehensive resource for organizations looking to leverage GenAI technologies effectively.