Zilliz - Provides a managed vector database service.
Cossmology Profile: https://dub.sh/HxFCcoG
Key People: Charles Xie, James Luan
Zilliz - Provides a managed vector database service.
Cossmology Profile: https://dub.sh/HxFCcoG
Key People: Charles Xie, James Luan

Learn what text embeddings are, how they power RAG and semantic search, and how to call embedding APIs from Python using Ollama or an OpenAI-compatible server (for example llama.cpp). Includes persistence, retrieval, and links to chunking, vector stores, and reranking on this site.
Databases for #AI: Should you use a vector #database? 🤔
This article compares #opensource projects competing to handle modern #AI workloads, including #machinelearning and #LLMs. Discover which databases best meet today’s AI challenges: https://lpi.org/636x
(Disclaimer: This post contains an AI-generated image.)
#AndyOram #AI #vectordatabase #machinelearning #LLMs #SQL #opensource #hybridsearch #generativeAI #MariaDB #MongoDB #Milvus #Qdrant #Weaviate #Vespa #ChromaDB #LanceDB

Your RAG’s Secret Backdoor: Leaking Data Through Vector Databases
This article exposes a vulnerability in Retrieval-Augmented Generation (RAG) systems, where misconfigured vector databases can lead to sensitive data leakage. By improperly securing these databases, attackers can gain access to internal documents such as HR policies and top-secret product roadmaps. The RAG system works by storing document chunks as embeddings in a special-purpose vector database and querying it to provide context for the LLM. The focus on securing the LLM while neglecting the vector database leaves it vulnerable to data exfiltration. The attacker can exploit weak access controls and clever retrieval attacks to gain access to sensitive data. Key lesson: Secure vector databases to prevent data breaches caused by RAG system vulnerabilities. #BugBounty #ArtificialIntelligence #DataLeak #Infosec #VectorDatabase
[zvec - 초경량·초고속 인프로세스 벡터 DB
Zvec는 초경량·초고속 인프로세스 벡터 DB로, Alibaba의 Proxima 엔진 기반으로 구축되어 대규모 유사도 검색을 최소 설정으로 수행하도록 설계되었습니다. 밀집 및 희소 벡터를 모두 지원하며, 하이브리드 검색 기능을 통해 의미적 유사도와 구조적 필터링을 결합한 정밀 검색을 제공합니다. C++ 기반 핵심 엔진과 SWIG·Python 바인딩 구조로 구성되어 고성능 연산과 다양한 언어 통합을 지원하며, Apache-2.0 라이선스로 제공됩니다.
https://news.hada.io/topic?id=27147
#vectordatabase #algorithms #machinelearning #opensource #search
via @dotnet : Vector Data in .NET – Building Blocks for AI Part 2
https://ift.tt/VtJUvye
#VectorData #NET #AI #BuildingBlocks #SemanticSearch #RAG #Embedding #Embeddings #VectorDatabase #Qdrant #Redis #CosmosDB #SQLServer #PostgreSQL #SQLite #InMemory #VectorSto…
Did you know? Our pgedge-vectorizer tool (on GitHub: https://github.com/pgEdge/pgedge-vectorizer) automatically chunks text content and generates vector embeddings with the help of background workers.
OpenAI, Voyage AI, and Ollama are supported as embedding providers, and a simple SQL interface allows you to enable vectorization on any table. (There’s even built-in views and functions for monitoring queue status.)
#github #opensource #semanticsearch #vector #vectordatabase #openai #ollama #voyageai

A PostgreSQL extension to create chunk tables for existing text data, and populate them with embeddings using your favourite LLM. - pgEdge/pgedge-vectorizer

Step-by-step RAG tutorial: build retrieval-augmented generation systems with vector databases, hybrid search, reranking, and web search. Architecture, implementation, and production best practices.