Following a merger that left the Australian fintech with a fragmented data architecture, Lendi Group has consolidated its ...

KIOXIA achieves 4.8 billion high-dimensional vector search database on a single server, with a significant reduction in index build time.

Kioxia Corporation today announced the successful demonstration of achieving high-dimensional vector search scaling to 4.8 billion vectors on a single server with its open-source KIOXIA AiSAQ(TM) ...

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 ...

A new open-source framework called PageIndex solves one of the old problems of retrieval-augmented generation (RAG): handling very long documents. The classic RAG workflow (chunk documents, calculate ...

Integration with leading vector database enables ease of adoption within the open-source community and taking full advantage of SSD-optimized vector search capabilities TOKYO--(BUSINESS WIRE)--Kioxia ...

TL;DR: KIOXIA's open-source AiSAQ technology reduces DRAM needs by offloading vectorized AI data to SSDs, enabling scalable, low-latency Retrieval Augmented Generation (RAG) pipelines. Its integration ...