Vector Database Stories
From company news to technical tutorials – explore the most popular content on the Zilliz blog.
Community
Producing Structured Outputs from LLMs with Constrained Sampling
Discuss the role of semantic search in processing unstructured data, how finite state machines enable reliable generation, and practical implementations using modern tools for structured outputs from LLMs.
Community
Insights into LLM Security from the World’s Largest Red Team
We will discuss how the Gandalf project revealed LLMs' vulnerabilities to adversarial attacks. Additionally, we will address the role of vector databases in AI security.
Community
Teaching LLMs to Rank Better: The Power of Fine-Grained Relevance Scoring
We’ll explore the limitations of binary relevance labels, how fine-grained relevance scoring works, and why it’s a game-changer for zero-shot text rankers
Community
Empowering Women in AI: RAG Hackathon at Stanford
Empower and celebrate women in AI at the Women in AI RAG Hackathon at Stanford. Engage with experts, build innovative AI projects, and compete for prizes.
Community
RocketQA: Optimized Dense Passage Retrieval for Open-Domain Question Answering
RocketQA is a highly optimized dense passage retrieval framework designed to enhance open-domain question-answering (QA) systems.
Engineering
Beyond PGVector: When Your Vector Database Needs a Formula 1 Upgrade
This blog explores why Postgres, with its vector search add-on, pgvector, works well for smaller projects and simpler use cases but reaches its limits for large-scale vector search.
Community
Semantic Search vs. Lexical Search vs. Full-text Search
Lexical search offers exact term matching; full-text search allows for fuzzy matching; semantic search understands context and intent.
Community
GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval
GPL is an unsupervised domain adaptation technique for dense retrieval models that combines a query generator with pseudo-labeling.
Community
Advancing LLMs: Exploring Native, Advanced, and Modular RAG Approaches
This post explores the key components of RAG, its evolution, technical implementation, evaluation methods, and potential for real-world applications.