Developing Cloud-Native Java AI applications with DJL and LangChain4J by Sébastien Blanc, Alex Soto

Large Language Models (LLMs) have become increasingly popular recently, and many models are now available, such as OpenAI, Llama, Gemma, Mistral, etc. These models can be incorporated into your enterprise code to enhance the customer experience by eliminating the need for customers to navigate through an entire website or improving the search process of on-site documentation.However, AI encompasses more than just LLMs; it includes fraud detection, image classification, sentiment analysis, and more. In this session, we will explore how to integrate Java with AI and large language models, covering topics like how to consume, train/retrain, and infer them. We’ll expand your knowledge beyond the typical chatbots to make your enterprise enter into the AI era.We will also demonstrate how to seamlessly deploy these models to Kubernetes, ensuring the deployment parameters are configured correctly or using tools like KNative to make your models more sustainable.If you are interested in hands-on experience with AI, LLMs, and Java, with a focus on practical applications rather than theory, then this session is for you. You do not require any prior knowledge of AI to attend.