Abstract
"Large Language Models (LLMs) are redefining analysis across structured and unstructured data, leading to the emergence of two primary architectural paradigms: AI or semantic engines, and data agents. Despite distinct approaches, both architectures encounter pivotal challenges, particularly in optimizing AI operators, agentic pipelines, natural language data interfaces, and AI-powered search. Centrally, embeddings and similarity search are key building blocks. This talk first addresses optimization for semantic operators, presenting an extensive evaluation of proxy models for AI query approximation. The findings demonstrate a greater than 100x cost and latency reduction for semantic filtering (AI.IF) and significant gains for semantic ranking (AI.RANK). Next, the talk examines Filtered Vector Search (FVS), a key component for semantic search and Generative AI (GenAI) applications in modern database systems. A central insight is that optimal algorithm selection is not determined solely by distance‑metric computation costs; rather, system‑level overheads play a substantial and decisive role. Finally, the talk highlights the discovery of relevant data sources as a major bottleneck and introduces a metadata reasoner agent to address this challenge."
About the speaker
"Fatma Özcan is a Principal Engineer at Systems Research@Google. Her current research focuses on GenAI and data management, vector search, platforms and infra-structure for large-scale data analysis, and natural language interfaces to
data. Dr Özcan got her PhD degree in computer science from University of Maryland, College Park, and her BSc degree in computer engineering from METU, Ankara. Before joining Google, she was a Distinguished Research Staff Member and a senior manager at IBM Almaden Research Center. She has over 24 years of experience in industrial research, and has delivered core technologies into various IBM and Google products. She is the co-author of the book ""Heterogeneous Agent Systems"", and co-author of several conference papers and patents. She is an ACM Fellow and serves on the CRA board of directors, and she is the co-chair of CRA-Industry. She received the VLDB Women in Database Research Award in 2022."
