LLMs and Spring: Building Smart Chat Applications with Redis

Track: Artificial Intelligence
Generative AI and the emergence of LLMs are radically changing content retrieval and generation industries. Using a combination of Natural Language Processing (NLP) techniques, foundation Machine Learning models (GPT and friends), and vector databases, chat-driven smart applications are changing the landscape of modern apps. This presentation explores the Retrieval-Augmented Generation (RAG) approach, which leverages semantic search to dynamically infuse factual knowledge into a large language model (LLM) prompt. This technique enables contextual augmentation of the LLM, enhancing its performance in various tasks such as answering questions, summarizing content, or generating new content. Redis, a vector database and full-text search engine, enables RAG workflows. In this session, we'll explore building RAG applications using Redis and Spring Boot.
Brian Sam-Bodden
Brian Sam-Bodden is a senior developer advocate at Redis as well as an author, instructor, speaker, and open source contributor and Java Champion who has spent over twenty years crafting software systems. He holds dual bachelor’s degrees from Ohio Wesleyan University in computer science and physics. Brian is a frequent speaker at user groups and conferences nationally and abroad and is the author of “Beginning POJOs: Spring, Hibernate, JBoss and Tapestry”, co-author of the “Enterprise Java Development on a Budget: Leveraging Java Open Source Technologies” and a contributor to O'Reilly's “97 Things Every Project Manager Should Know”.