Introducing Ray AI Runtime: Open-Source Toolkit for Scalable ML Applications

Explore the open-source toolkit Ray AI Runtime (AIR) for building scalable and programmable end-to-end machine learning applications in this 33-minute conference talk. Dive into the functionality and features of Ray AIR, which leverages Ray and its library ecosystem to enhance ML platforms. Examine benchmarks that demonstrate the utility of this toolkit and gain insights into how it can improve your machine learning workflows. Learn how Ray AIR brings scalability and programmability to ML platforms, potentially revolutionizing your approach to building machine learning applications.