Vector Database Stories
From company news to technical tutorials – explore the most popular content on the Zilliz blog.
Product
New for Zilliz Cloud: 10X Performance Boost and Enhanced Enterprise Features
A 10x faster Performance with Cardinal vector search engine, production-ready features including Multi-replica, Data Migration, Authentication, and more
Community
Learn Llama 3.2 and How to Build a RAG Pipeline with Llama and Milvus
introduce Llama 3.1 and 3.2 and explore how to build a RAG app with Llama 3.2 and Milvus.
Community
LoRA Explained: Low-Rank Adaptation for Fine-Tuning LLMs
LoRA (Low-Rank Adaptation) is a technique for efficiently fine-tuning LLMs by introducing low-rank trainable weight matrices into specific model layers.
Engineering
Deploying a Multimodal RAG System Using vLLM and Milvus
This blog will guide you through creating a Multimodal RAG with Milvus and vLLM.
Community
Transformers4Rec: Bringing NLP Power to Modern Recommendation Systems
Transformers4Rec is a powerful and flexible library designed for creating sequential and session-based recommendation systems with PyTorch.
Community
How Inkeep and Milvus Built a RAG-driven AI Assistant for Smarter Interaction
Robert Tran, the Co-founder and CTO of Inkeep, shared how Inkeep and Zilliz built an AI-powered assistant for their documentation site.
Product
Safe RAG with HydroX AI and Zilliz: PII Masking for Responsible GenAI
Organizations can ensure privacy at every layer of their data pipeline by anonymizing or masking PII using the PII Marker before data reaches the vector database.
Community
Getting Started with Voyager: Spotify's Nearest-Neighbor Search Library
Voyager: a new open-source library for fast nearest-neighbor searches. Voyager uses the HNSW algorithm, outperforming its previous library, Annoy.
Community
XLNet Explained: Generalized Autoregressive Pretraining for Enhanced Language Understanding
XLNet is a transformer-based language model that builds on BERT's limitations by introducing a new approach called permutation-based training.