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Explore the challenges and architectural changes made to Ray, a distributed execution engine for scaling Python applications, to support large-scale data processing workloads. Learn about the key developments implemented over the past year to enhance Ray's capabilities in machine learning and data processing applications. Gain insights into the evolving landscape of scalable Python programming and discover how Ray addresses the growing demand for efficient distributed computing solutions.
