Foojay Podcast #47: Artificial Intelligence and Machine Learning with Java
ChatGPT changed the way many of us think about software, but the Java ecosystem already has the tools to join in. Frameworks like LangChain4j make it possible to wire large language models into real applications without leaving the JVM. In this Foojay Podcast #47, we sat down with Lize Raes and Lutske de Leeuw to talk through what AI and machine learning look like from a Java developer’s chair.
What we talked about
- Foundational concepts behind AI and machine learning
- The LangChain4j framework and what it enables
- How large language models help structure and query data
- How developer workflows shift in the AI era
- Privacy questions around feeding code to AI models
- Data labeling for machine learning models
- Cost trade-offs between hosted APIs and local systems
- Building a chat UI and the rough edges that come with it
- Comparisons between the AI hype cycle and earlier waves like blockchain
- AI applications for sustainable development
- Java platform work like Project Sumatra and Project Panama
- GPU acceleration through TornadoVM
Why it matters
AI is not a separate stack you have to learn from scratch. Java already plugs into this world, and projects like LangChain4j and TornadoVM give us a clear path forward. The conversation grounds the hype in concrete trade-offs around cost, privacy, and developer experience.
See the Foojay Podcast #47 for all info, shownotes, links, etc.