TweakTown

KIOXIA achieves 4.8 billion vector sector on a single AI server with minimal DRAM

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

Bauhaus: Restructuring Vector Database for LLM Retrieval on CXL-Based Tiered Memory

Abstract: Retrieval-augmented generation pipelines store large volumes of embedding vectors in vector databases for semantic search. In Compute Express Link (CXL)-based tiered memory systems, ...
Oak Ridge National Lab

Oak Ridge National Laboratory launches the Next-Generation Data Centers Institute

In response to the societal challenge of growing electricity demand from AI data centers, Oak Ridge National Laboratory (ORNL) is launching the Next Generation Data Centers Institute (NGDCI). This ...
marktechpost

How to Build an Elastic Vector Database with Consistent Hashing, Sharding, and Live Ring Visualization for RAG Systems

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 ...
IEEE

Enhancing Vector Data Quality through Negative Learning for Retrieval-augmented Large Models

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 ...