About this Event
Java powers much of the financial world. Now it's time to put AI to work on the JVM.
Fraud detection, risk analysis, and real-time financial decisions demand more than accurate models. They require high throughput, low latency, predictable performance, and enterprise-grade security. And they need to work with the Java applications and infrastructure already running the business.
In this session, we'll explore how modern Java delivers high-performance AI without leaving the JVM. We'll cover GPU acceleration with the Foreign Function & Memory API, CPU optimization with the Vector API, and efficient model inference for workloads where LLMs are too slow, too expensive, or the wrong tool.
Using a real-world fraud detection scenario, we'll demonstrate how Java developers can build and deploy fast, scalable AI solutions using familiar tools, frameworks, and infrastructure.
6:00-6:30pm Pizza/refreshments
6:30-8:00pm Using Java for Fraud Detection without an LLM
Zoran Ševarac is a Java Champion, AI and machine learning expert, and CEO of Deep Netts, where he focuses on making AI faster and more accessible to Java developers.
He is a Full Professor at the University of Belgrade, leading its Laboratory for Artificial Intelligence. With over 20 years of experience, Zoran created the award-winning Neuroph neural network framework, co-authored JSR 381 (Visual Recognition API), and serves on the Java Community Process Executive Committee and its AI Working Group. A longtime Java community contributor, he is a frequent speaker at JavaOne, Devoxx, QCon, and other major developer conferences.
Event venue & nearby stays
307 W 38th St, 307 West 38th Street, New York, United States
Concerts, fests, parties, meetups — all the happenings, one place.