Join James Luan, VP of Engineering at Zilliz, for an exclusive deep dive into the latest release of the open-source vector database Milvus 2.6. Built for AI workloads at scale, Milvus 2.6 introduces major architectural improvements that dramatically reduce storage, compute, and operational costs—without compromising on performance. In this session, you'll learn: * New Features for All Users: How tiered storage, vector quantization, and a diskless WAL (with Woodpecker) can cut infrastructure costs by up to 10X—ideal for scaling AI workloads affordably. * For Existing Users: How Milvus 2.6 simplifies your operations with new features like CDC + BulkInsert for easier data replication and native package support that streamlines installation and upgrades (no more manual dependencies or setup headaches!). * How Milvus 2.6 increases developer productivity with built-in tools for ingestion, advanced search, analytics, and reranking—making it easier than ever to iterate and deploy your AI applications. What's next on the Milvus roadmap: Insights into future enhancements and how they’ll further streamline your workflows. Whether you're just starting with vector search, building GenAI applications, or managing multimodal data, Milvus 2.6 offers significant advantages that can scale with your needs.