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Chad Armor

• Celebrated Java 26 release date
• Preview of a documentary about the creation of Java coming out in the summer
• Java 26 goals – Data oriented programming, Java in the small (scriptable/learnable), Java at global scale, Integrity by default, AI at Java scale

George Saab

• Showed JEPs in Java 26
• For new learners java playground (now supports java 26), oracle vs code extension (can share snippets of code, notebook support)
• Oracle Java Verified Portfolio (JVP). For paid customers including OCI customers includes private support for Java FX, VS Code Java extension, Helidon
• Support for Java 8 ends March 2028, Java 17 ends September 2028, Java 25 through September 2030
• Project proposal Detroit: combine JavaScript/Python snippets with Java. Can call libraries not available in Java. Was on hold becuase was waiting on Panama project
• Java and AI – readability/compatabiliy, clean semantic model/static tiyping, Java’s specs/docs/JEPs, JVM performance/tools

Ana Maria Mihalceanu and Lize Raes

• Didn’t take notes. It was short

Uber (didn’t catch name)

• Michelangelo – Uber’s unified E2E ML platform. 20K models trained per month 5.3K models in production, 40M peak predications per second. Suppported by less than 10 engineers. Java 8 to 11 reduced CPU by 15% and Java 11 to 21 another 11% reduction.
• GPUs to scale – 10-100x traffic amplification

NVIDIA (Ikroop Dhillon)

• Partnering with Java architects at Oracle for many years about Panama
• NVIDIA conference in San Jose. Yesterday talked about AI including partnering with OpenClaw to make it more secure.
• Worlds AI runs on NVIDIA
• Java historically focused on CPU based development. Environment more complex due to acceleration
• Unstructured data is context of AI
• NVIDIA cuVS Java/Lucene powers Java Vector Search ecosystem. Went from hours to minutes.
• NVIDIA NIM – containerized/packaged model

Lize Raes

• Listed Java frameworks for AI
• Rod Johnson is sick – created Embabel.

Spring (Josh Long)

• Used Spring Initiallzr
• Noted Java 25 was latest as of time of the recording
• Used this java script.java being the first good java script joke
• Showed his AI example very quickly. [glad i had seen this before]
• Showed JVM fastest in benchmark against other langauges
• Also covered Rod Johnson’s part. It was a subset of those at his DevNexus keynote so didn’t take notes again. See https://www.selikoff.net/2026/03/05/devnexus-2026-its-up-to-java-developers-to-fix-enterprise-ai/ for those notes

Ana Maria Mihalceanu and Lize Raes

• Example of a help desk system
• more to comeLook at what AI can help with – ex: add context to ticket, classification, code fixes, flagging urgency
• vs humans for clarification, compliance gatekeeping, accountability, exception handling
• AI triage classifies ticket using similar tickets and company RAG
• AI coding assistant proposes fix
• Important for Enterprise AI: human must approve pull requests and gets final approval on integrating into workflow. Also, must be easily revertable

Ana Maria Mihalceanu

• Typed contracts
• AI components behave like standard services
• Existing security/permissions
• Lots of libraries for AI

Paul Sandoz (Java Libraries Architect)

• “Java is *often* where AI needs to be”
• “Java is *almost* everywhere AI needs to be”
• Java in a good positionf or AI
• Need more than AI. ex: code that converts to text to tkens, connect models to info sources (vector/relational databases), manage interactions among models
• JEPs for performance improvement. Sometimes behind the sense like aliasing venctors to improve speed.
• Most models are Python wrappers around C/C++ code
• Pain points become solutions/jeps/new features.
• Pain point: Using GPUs is too hard
• Pain point; Developing maching learning models is difficult
• Solutions: foundational building blocks in JDK, build libraries with (ex: GPU support), for building apps with (Java code running on GPU)
• JEP-500: prepare for final to mean final (vs reflection)
• Project Babylon – need to translate Java code into other languages
• HAT (Heterogeneous Accelerator Toolkit) – develop Java code that represents GPU code so can run/debug on JVM. Part of Babylon
• Project Detroit – tried in past but never got off the ground. Still strong interest in Java/JavaScript integration. And now Python interest as well. Will use widely used implementations for integration rather than integrating from scratch (v8 and CPython). Uses Panama
• Project Panama is to foreign libraries as Project Detorit is to foreigtn language runtimes
• Goal: java is everywhere AI needs to be

Microsoft (Patrick Chanezon, Brian Benz)

• AI transformations stats – decrase median code review turnaround, faster test automation, etc
• AI as a superpower: https://www.oreilly.com/radar/the-end-of-programming-as-we-know-it/
• GitHub Copilot – autocomplete
• Then added chat
• Then added agent mode – background
• AI agent – loop with LLM in middle
• Need to build and become productive teammates as become manager of agents
• Microsoft Foundry – has models available. Mix of open source and closed. Processed 100T tokens quarterly
• Microsoft IQ – sits on top of Office
• Copilot now has an SDK https://github.com/github/copilot-sdk-java
• Showed modernizing a Java 5/Struts app with Copilot. Lets choose from a list of models
• Agenta at different points in lifecycle – ex: SRE
• More stats: 93% of globabl engineering team uses Copolit. and copilot is #1 contributor to copilot.

My take

Good range of topics for an opener including a good mix of Oracle and external companies