AI Testing
MAIN TRACK TALK
Taming Testing of AI apps
As AI applications become increasingly integrated into critical applications, ensuring their reliability, safety, and fairness is more challenging than ever. Unlike traditional software, AI models are dynamic and data-driven and often behave unpredictably in real-world scenarios. This makes testing AI systems a complex endeavour that requires specialised approaches.
In this talk, you will explore the unique challenges of testing AI applications, such as handling probabilistic outputs, bias detection, model drift, and transparency in decision-making. You’ll also cover how to use AI to develop better tests or generate synthetic data to make tests more real than random data.
What you’ll learn
From this talk you will learn how to:
Session details
Alex Soto
Alex Soto is a Director of Developer Experience at Red Hat. He is passionate about the Java world, software automation and he believes in the open-source software model. Alex has co-authored four books “Testing Java Microservices,” “Quarkus Cookbook,” “Kubernetes Secrets Management,” “GitOps Cookbook”, and “RHCE Ansible Automation Study Guide”, and “ Applied AI for Enterprise Java Development” Recognized as a Java Champion since 2017, Alex is an esteemed international speaker who shares his knowledge and expertise at conferences and events worldwide. He also collaborates on radio at Onda Cero and imparts sessions as a teacher at Salle URL University.