Explore an innovative RDMA-based ordered key-value store using remote learned cache in this USENIX OSDI '20 conference talk. Dive into the design and implementation of XSTORE, which combines a tree-based index at the server for dynamic workloads with a learned cache at the client for static workloads. Learn how this hybrid architecture leverages machine learning models as a cache structure for tree-based indexes, decoupling model retraining from index updating. Discover how XSTORE achieves impressive performance, outperforming state-of-the-art RDMA-based ordered key-value stores by up to 5.9 times. Understand the challenges of implementing learned caches and the solutions employed, including handling stale models and ensuring correctness through validation mechanisms. Gain insights into the memory-performance tradeoffs and the potential for significant client-side memory savings.