Dimitris has 25 years of experience in IT and he is currently Director of Engineering at Red Hat in charge of the Cloud Native Runtimes group that includes Quarkus, Vert.x, SpringBoot, Node.js, as well as his former WildFly / JBoss Enterprise Application Server teams that he used to run for several years. He also served as the JBoss AS project lead and he has been a JBoss addict and contributor from the early start-up days. He worked previously at Intracom and Motorola in the areas of NMS/OSS, designing reusable frameworks and distributed systems. Dimitris studied computer science at the Technological Educational Institute of Athens and received an M.Sc. by research from University College Dublin, Ireland.
Dimitris is a passionate advocator of Opensource & Red Hat technologies and has presented on a variety of events and conferences around the world. He has been an invited speaker at various Java/Linux community events and user groups, and he has delivered inspirational talks on technology and Open Source in universities and educational institutes. In his spare time he has also helped with the organization of technology enablement events for children, like Scratch Days, Devoxx4Kids and JCrete4Kids.
Come to our BOF to discuss with members of the Quarkus & LangChain4j communities the present and future of our popular projects!
Generative AI has taken the world by storm over the last year, and it seems like every executive leader out there is telling us “regular” Java application developers to “add AI” to our applications. Does that mean we need to drop everything we’ve built and become data scientists instead now?
Fortunately, we can actually infuse AI models built by actual AI experts into our applications in a fairly straightforward way, thanks to some new projects out there. We promise it’s not as complicated as you might think! Thanks to the ease of use and superb developer experience of Quarkus and the nice AI integration capabilities that the LangChain4j libraries offer, it becomes trivial to start working with AI and make your stakeholders happy 🙂
In this session, you’ll explore a variety of AI capabilities. We’ll start from the Quarkus DevUI where you can try out AI models even before writing any code. Then we’ll get our hands dirty with some code and exploring LangChain4j features such as prompting, chaining, and preserving state; agents and function-calling; enriching your AI model’s knowledge with your own documents using retrieval augmented generation (RAG); and discovering ways to run (and train) models locally using tools like Ollama and/or Podman AI Lab. In addition, we’ll take a look at observability and fault tolerance of the AI integration and compile the app to a native binary. Maybe we’ll even try some new features, such as generating images or audio!
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