Foojay Webinar Live Stream: Java’s Place in the AI Revolution
- April 28, 2025
- 26840 Unique Views
- < 1 min read
This first online Foojay Webinar highlights Java's place in the AI revolution, focusing on exploring AI/ML using pure Java tools.
AI and Machine Learning (ML) are becoming essential in modern software development. For Java developers, there's no need to switch technology stacks. It's now possible to build, train, and deploy ML models using tools available directly within the Java ecosystem.
This webinar focuses on practical predictive AI/ML approaches in pure Java. We’ll walk through key Java libraries, show how to structure and train models, and discuss how Java’s core strengths, ie, JVM performance, type safety, and enterprise integration, can be used to build scalable AI solutions.
If you're a Java developer or architect interested in learning more about AI/ML with structured data, this session will show you how to do it efficiently using native Java tools.
Guests
Frank Greco
Senior AI/ML Consultant, Technology Strategist, Java Champion, Developer Ecosystem (Crossroads)
Zoran Sevarac
CEO of @Deep Netts, Full Professor at University of Belgrade, Java Champion, AI Consultant | Deep Learning Development Platform
Moderator
Pratik Patel
VP Developer Advocacy at Azul, Java Champion
Links
- LinkedIn Course: Foundations of AI and Machine Learning for Java Developers
- Demo on Github: https://github.com/deepnetts/CreditCardFraudDetection
- Free Deep Netts Download: https://www.deepnetts.com/download-latest, free for development, prototyping and education
- Join Linkedin Group AI/ML for Java Ecosystem: https://www.linkedin.com/groups/10084933/
- Quick Survey for future webinars: https://forms.gle/RfskNfohaKkhP15Q9
Slides
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Frank Delporte is a Java Champion, Java Developer, Technical Writer at Azul, Blogger, Author of "Getting started with Java on Raspberry Pi", and Pi4J Contributor. Frank blogs about his experiments with Java and JavaFX, sometimes combined with electronic components, on the Raspberry Pi.
VP Developer Advocacy at Azul
Zoran is an artificial intelligence software developer, entrepreneur, Java Champion, and researcher. He's the creator of the popular and award winning educational Java open source neural network software Neuroph and the deep learning platform Deep Netts.
Comments (2)
Tobiloba
3 years agoI see that you save the point of interest as text in the DB but the response gotten from ChatGPT is JSON. Does this mean you convert the response into string using libraries like gson before saving it in the database?
Denis Magda
3 years agoHey, The response is a String object in the JSON format [1]. The repository takes this JSON string as is and stores to the database [2]. Presently, Spring Data auto-generates the CREATE TABLE statement on the startup and sets the "point of interest" column's type to "text" (or "varchar", don't remember). However, it's always possible to ask Spring Data to use the "json" or "jsonb" type for the column if you wish to query the JSON at the database level. Finally, Vaadin displays a list of PointsOfInterests. Those are generated using the org.json library [3]. Let me know if you have other questions. Hope this helps. [1] https://github.com/YugabyteDB-Samples/budget-journey-gpt/blob/main/src/main/java/com/yugabyte/com/TripsAdvisorService.java#L103 [2] https://github.com/YugabyteDB-Samples/budget-journey-gpt/blob/main/src/main/java/com/yugabyte/com/TripsAdvisorService.java#L74 [3] https://github.com/YugabyteDB-Samples/budget-journey-gpt/blob/main/src/main/java/com/yugabyte/com/TripsAdvisorService.java#L114