If you couldn’t make it to GTC this year, you could still find plenty of AI at JavaOne. About 400 people attended the keynote in person, with more online.

That keynote was “Java for an AI World.”  Oracle thinks Java is a great programming language for AI, and they claim their strength over other languages is that they’ve kept careful documentation — they have a large body of public specifications, decision documents and Javadoc for AI to ingest. During the keynote, Oracle demonstrated an AI development process, making it clear to its audience of developers that AI-assisted workflows included humans in the loop. They’re betting that developers will manage agents but take responsibility and accountability for what ships.

The Java runtime itself isn’t standing still. New Oracle features allow better integration with GPUs and code translation from Java to GPU-specific languages like CUDA. On the framework front, Oracle is reintroducing commercial JavaFX support. They’re also aligning the releases of Helidon, JavaFX and their VisualStudio Code plugin with the JDK release.

Oracle announced they’ve restarted Project Detroit, which should lead to closer integration with foreign AI libraries and tools, starting with JavaScript using V8 and Python using CPython. In concert with Project Panama, this will give Java the ability to access AI technologies written in languages outside the Java ecosystem. After Project Detroit ships, expect to see lots of Java wrappers around the cool libraries that developers use in other environments.

Java Is A Floor Wax And A Dessert Topping

However, Oracle’s view of Java — the Java virtual machine, class library, and language itself as a single entity — may constrain it. People have already been experimenting with going directly from prompts to Java bytecode. Despite the improvements Oracle has been making in the language and onboarding experience for new developers, the current AI focus is on runtime.

That’s not to say there haven’t been important language improvements — Oracle wants people to use Java as a teaching and scripting language, introducing new language features to support that. What Oracle didn’t address is why choice of programming language is important in an AI age. In fact, one point made during the keynote was, when Java bindings didn’t exist, you could just convert Python bindings to Java using AI. Given that, what keeps you from going the other way? Oracle points to their robust and proven ecosystem — and Java’s mature runtime and class library are its biggest selling points at enterprises, more than the language itself.

Businesses That Use Java Are Cautious

The pressures that keep people on Java are similar to the pressures that keep them from embracing AI with the same alacrity as, say, Python or Go developers. Through Java’s life, Oracle has done an excellent job of delivering new Java features with few changes that break existing code. When I talked with developers at JavaOne, they seemed interested in AI, but many felt constrained by their organizations. More than one told me they’d like to adopt more AI but couldn’t get approval from other business stakeholders. Of course, at the enterprises where they work, Java developers are the guardians of the crown jewels.

In the end, Oracle will have to show that a disruptive technology like AI can deliver real value without disrupting the business. Java developers are excited to get their hands on AI technology and are looking for guidance on best practices. Oracle gave developers a taste of this at JavaOne and educating developers is a move in the right direction. That said, Java is a little behind on AI. Oracle must make sure AI developers in Java’s ecosystem have the same tools as their Python peers. Moreover, Oracle will need to convince other corporate stakeholders by case studies and by their own example, that it’s possible and safe to integrate AI into an enterprise Java application in a way that provides business value.

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