Qdrant's $50M Series B and version 1.17 release make the case that agentic AI didn't simplify vector search — it scaled the ...

Overview: Free YouTube channels provide structured playlists covering AI, ML, and analytics fundamentals.Practical coding demonstrations help build real-world d ...

Abstract: Vector databases typically manage large collections of embedding vectors. As AI applications are growing rapidly, the number of embeddings that need to be stored and indexed is increasing.

In this tutorial, we build an elastic vector database simulator that mirrors how modern RAG systems shard embeddings across distributed storage nodes. We implement consistent hashing with virtual ...

Endee.io launches Endee, an open source vector database delivering fast, accurate, and cost-efficient AI and semantic search at scale. Endee rethinks vector DBs for high recall, low latency, and low ...

Abstract: Retrieval-augmented Large Models (RALMs) have emerged as a promising paradigm to enhance large language models (LLMs) by integrating external knowledge. However, the inherent complexity of ...

VittoriaDB is a high-performance, embedded vector database designed for local AI development and production deployments. Built with simplicity and performance in mind, it provides a zero-configuration ...