Quarkus and AI. Integrating Java and LLM to build intelligent applications.

Track: Cloud Native
A Large Language Model (LLM) is a component of artificial intelligence specifically designed to comprehend and generate text that closely resembles human language based on the input it receives. One common scenario where it finds utility is when it needs to generate Java code to address a problem or create Kubernetes manifests with specific features. However, LLMs can also be employed with your enterprise code to enhance the customer experience, eliminating the need for customers to navigate through an entire website or improving the search process of on-site documentation During this session, we will explore how to integrate Quarkus with Large Language Models to establish a novel interaction interface for your users so they feel more human than just clicking across links. It's important to note that while Quarkus plays a significant role in this discussion, the concepts presented also apply to other Java frameworks. If you're interested in hands-on experience with Large Language Models and Java, with a focus on practical applications rather than theory, then this session is for you.
Alex Soto
Alex Soto is a Director of Developer Experience at Red Hat. He is passionate about the Java world, software automation and he believes in the open-source software model. Alex is the co-author of Testing Java Microservice, Quarkus cookbook, Kubernetes Secrets Management, and GitOps cookbook books and contributor to several open-source projects. A Java Champion since 2017, he is also an international speaker and teacher at Salle URL University. You can follow him on Twitter (@alexsotob) to stay tuned to what’s going on in Kubernetes and Java world.