
airhacks.fm podcast with adam bien Babylon and java.util.json
Oct 26, 2025
Paul Sandoz, a Java platform engineer at OpenJDK, discusses the exciting evolution of Java, touching on energy efficiency and performance improvements. He dives into Project Babylon and its integration with Vector API, enabling advanced AI capabilities on the JVM. Listeners will learn about TornadoVM's GPU optimizations, Python's enterprise challenges, and the introduction of a minimal JSON API for OpenJDK. Paul shares insights on pattern matching and the benefits of a lightweight API, making Java a more competitive option for enterprise and embedded systems.
AI Snips
Chapters
Transcript
Episode notes
TornadoVM's GPU Inference Breakthrough
- TornadoVM researchers moved data pointers to keep tensors on the GPU and avoid transfer overhead, yielding large inference gains.
- Adam Bien reports 6–10x speedups on NVIDIA and ongoing Metal work for Apple Silicon.
Java's Enterprise Advantage For AI
- Java can be a strong production platform for AI because enterprises already standardize on Java tooling and packaging.
- Paul Sandoz argues multiple integration paths (pure Java, Panama, Tornado, Onyx) increase adoption choices.
Prefer Java For Production Packaging
- Favor Java for production AI when you need reliable packaging, security checks, and easier deployment.
- Use Java's single-jar packaging or native options to avoid Python dependency complexity in enterprise environments.
