This video from AWS re:Invent 2023 explores how to build production-ready semantic search and retrieval-augmented generation (RAG) applications. Speakers from Elastic, AWS, and Adobe discuss the challenges of integrating private data with large language models securely and at scale. They cover key components like vector search, natural language processing, and data security. Elastic demonstrates how their Elasticsearch Relevance Engine provides comprehensive capabilities for vector search, hybrid search, and data processing in a single API. AWS highlights their Amazon Bedrock service for accessing foundation models. Adobe shares a real-world use case of enriching e-commerce product catalogs using domain-specific language models. The speakers emphasize the importance of having a flexible platform to experiment with different approaches as generative AI applications evolve.