We're in a new era of software development driven by Machine Learning (ML), a subset of AI that predicts or generates results by analyzing large datasets and recognizing patterns. Combined with Java, ML can generate code, query unstructured enterprise documents, summarize emails, offer bug triage strategies, predict GC issues, and identify library inconsistencies. This new phase offers exciting opportunities to boost productivity but also raises concerns for developers and enterprises. This session will cover AI/ML fundamentals, compare GenAI and PredAI, JSR #381 VisRec, prompt strategies, APIs, chatbot architecture, vector databases, and RAG strategies. We'll also explore REST-based APIs like Langchain4J, share advanced prompt techniques, and guide you on how to work with an LLM. Whether you're new or experienced with Java, you’ll find our code demos informative, highlighting where to apply GenAI effectively and where to avoid it. Presented by Frank Greco (NYJavaSIG Chair) at JavaOne 2025 (CA, March 2025). All JavaOne 2025 talks ➤ https://www.youtube.com/playlist?list=PLX8CzqL3ArzVV1xRJkRbcM2tOgVwytJAi Tags: #Java #AI #ML #JavaOne SES1126