Discover how to build responsive AI systems that react to real-time data using event-driven architectures. This beginner-friendly session introduces Atlas Stream Processing as your foundation for creating dynamic AI applications that process continuous data streams and adapt to changing conditions. You’ll learn practical approaches to:

Understanding event-driven design principles for AI applications Processing data streams for real-time ML predictions Building resilient pipelines that handle errors gracefully Implementing simple event patterns for common AI use cases Monitoring your AI systems effectively

Through straightforward examples and demonstrations, we’ll cover essential patterns that work for recommendation engines, anomaly detection systems, and personalization features. No advanced streaming knowledge required!

Join us to see how combining event-driven thinking with Atlas Stream Processing can transform your AI implementations from static batch processes to dynamic, responsive systems that deliver immediate value.