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
Training Text Embeddings with Jina AI
In a recent talk by Bo Wang, he discussed the creation of Jina text embeddings for modern vector search and RAG systems. He also shared methodologies for training embedding models that effectively encode extensive information, along with guidance o
Community
Unstructured Data Processing from Cloud to Edge
Edge computing brings data processing closer to the source on small devices; vectorDBs empower them to handle the growing unstructured data in real-time.
Community
A Different Angle: Retrieval Optimized Embedding Models
This blog will demonstrate how GCL can be integrated with Milvus, a leading vector database, to create optimized Retrieval-Augmented Generation (RAG) systems.
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.
Case Study
Generative AI for Creative Applications Using Storia Lab
This post discusses how Storia AI generates and edits images through simple text prompts or clicks and how we can leverage Storia AI and Milvus to build multimodal RAG.
Community
Build Better Multimodal RAG Pipelines with FiftyOne, LlamaIndex, and Milvus
Enhance the capabilities of multimodal systems by efficiently leveraging text and visual data for improved data retrieval and context-rich responses.
Community
Build RAG with LangChainJS, Milvus, and Strapi
A step-by-step guide to building an AI-powered FAQ system using Milvus as the vector database, LangChain.js for workflow coordination, and Strapi for content management
Community
How Vector Databases are Revolutionizing Unstructured Data Search in AI Applications
Learn how vector databases have emerged as a transformative technology in the field of AI and machine learning, particularly for handling unstructured data. Their applications extend far beyond simple retrieval-augmented generation (RAG) systems, revolutionizing various domains including customer support, recommendation systems, drug discovery, and multimodal search.