As AI systems continue to scale, observability has become an essential component for success. This webinar explores two key dimensions: data observability, which focuses on monitoring and improving the quality of data that drives AI systems, and AI observability, which provides transparency and accountability for model performance and decision-making.
Learn practical strategies for building "glass box" AI systems where insights are clear, issues are easy to diagnose, and scalability is seamless.
YOU'LL LEARN
1️⃣ Understand Data Observability: Learn how to implement monitoring systems to ensure high-quality, reliable data pipelines for AI systems.
2️⃣ Explore AI Observability: Discover tools and techniques for monitoring AI models, ensuring they are transparent, unbiased, and explainable.
3️⃣Bridge the Gap: Integrate data and AI observability practices to achieve robust, scalable, and trustworthy AI deployments.
Panelists to be announced soon
REGISTER HERE
