Modern AI and vector search are rapidly converging, forming a promising research frontier in intelligent information systems. On one hand, advances in AI have substantially improved the semantic accuracy and efficiency of vector search, including learned indexing structures, adaptive pruning strategies, and automated parameter tuning. On the other hand, powerful vector search techniques have enabled new AI paradigms, notably Retrieval-Augmented Generation (RAG), which effectively mitigates challenges in Large Language Models (LLMs) like knowledge staleness and hallucinations. This mutual reinforcement establishes a virtuous cycle where AI injects intelligence and adaptive optimization into vector search, while vector search, in turn, expands AI's capabilities in knowledge integration and context-aware generation. This tutorial provides a comprehensive overview of recent research and advancements at this intersection. We begin by discussing the foundational background and motivations for integrating vector search and AI. Subsequently, we explore how AI empowers vector search (AI4VS) across each step of the vector search pipeline. We then investigate how vector search empowers AI (VS4AI), with a particular focus on RAG frameworks that integrate dynamic, external knowledge sources into the generative process of LLMs. Furthermore, we analyze end-to-end co-optimization strategies that fully unlock the potential of the ``virtuous cycle" between vector search and AI. Finally, we highlight key challenges and future research opportunities in this emerging area. This paper was published in ICDE 2026.

翻译：现代人工智能与向量搜索正快速融合，在智能信息系统中形成了一个前景广阔的研究前沿。一方面，AI的进步显著提升了向量搜索的语义准确性和效率，包括学习型索引结构、自适应剪枝策略和自动化参数调优。另一方面，强大的向量搜索技术催生了新的AI范式，尤其是检索增强生成（RAG），它有效缓解了大型语言模型（LLMs）中知识陈旧和幻觉等挑战。这种相互促进建立了一个良性循环：AI为向量搜索注入智能和自适应优化能力，而向量搜索则反过来扩展了AI在知识整合和上下文感知生成方面的能力。本教程全面概述了该交叉领域的最新研究和进展。我们首先讨论向量搜索与AI融合的基础背景和动机。随后，我们探讨AI如何在向量搜索流程的每个步骤中赋能向量搜索（AI4VS）。接着，我们研究向量搜索如何赋能AI（VS4AI），特别关注将动态外部知识源集成到LLMs生成过程中的RAG框架。此外，我们分析了端到端协同优化策略，这些策略充分释放了向量搜索与AI之间“良性循环”的潜力。最后，我们指出了这一新兴领域的关键挑战和未来研究机遇。本文发表于ICDE 2026。