Java Language & PlatformConference50min
Java and the Next Generation of Programming Models
The session explores using Java to bridge external runtimes and AI models without glue code. It covers the Foreign Function and Memory API and jextract for safe native interaction, then Project Babylon’s code reflection to express, transform, and lower AI models directly in Java for accelerator-backed inference.
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Ana-Maria MihalceanuOracle
Lize RaesJava Platrform Group - Oracle
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Friday, October 9, 11:50-12:40
TBA 5
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Modern software increasingly interacts with AI models, query languages, and other specialized programming models, forcing you to switch contexts, embed foreign code, or write verbose wrappers to bridge the gap. What if you could express logic from outside the JVM directly in Java?
In this session, we start by looking at how Java enables you to safely interact with runtimes outside of the JVM using the Foreign Function and Memory API and tools like jextract.
Then will push further with Project Babylon’s code reflection: express AI models as Java programs that Babylon can analyze, transform and lower to inference engines, thus leveraging hardware accelerator backends while skipping external model files or the need to glue code.
Along the way, you will learn how to build expressive FFM-based inference today and author pure Java AI-ready models with Code Reflection tomorrow!
In this session, we start by looking at how Java enables you to safely interact with runtimes outside of the JVM using the Foreign Function and Memory API and tools like jextract.
Then will push further with Project Babylon’s code reflection: express AI models as Java programs that Babylon can analyze, transform and lower to inference engines, thus leveraging hardware accelerator backends while skipping external model files or the need to glue code.
Along the way, you will learn how to build expressive FFM-based inference today and author pure Java AI-ready models with Code Reflection tomorrow!
Ana-Maria Mihalceanu
Ana is a Java Champion Alumni and Senior Developer Advocate for the Java Platform Group at Oracle, with an extensive background in Java and cloud development. More recently, her work has expanded to explore how machine learning and AI can be applied within the Java ecosystem, helping Java developers adopt emerging capabilities while continuing to benefit from the stability, tooling, and performance of the Java Platform. She actively supports the growth of technical communities through knowledge sharing and enjoys curating content for conferences as a program committee member.
Lize Raes
Lize Raes loves helping developers to bring AI into real-world applications. As Developer Advocate for Java + AI at Oracle and collaborator at LangChain4j, she’s invested into making cutting-edge tech accessible and useful for developers. Her path has taken her from cochlear implant research to advising the Belgian government during COVID-19, to bioinformatics for drug development. Lize likes her projects hands-on and slightly unconventional, especially when they help make the world a bit better. Outside of work, you’ll find her behind the piano or in her woodworking atelier.