#vector-database

[ follow ]
#semantic-search #rag #approximate-nearest-neighbor #milvus #ai-applications #performance-optimization
Data science
fromMedium
8 hours ago

IVF vs HNSW Indexing in Milvus

Approximate Nearest Neighbor indexes in Milvus enable fast vector searches, achieving over 95% recall with significantly higher throughput compared to brute-force methods.
fromInfoQ
3 months ago

Pinecone Introduces Dedicated Read Nodes in Public Preview for Predictable Vector Workloads

Pinecone recently announced the public preview of Dedicated Read Nodes (DRN), a new capacity mode for its vector database designed to deliver predictable performance and cost at scale for high-throughput applications such as billion-vector semantic search, recommendation systems, and mission-critical AI services. This capability builds on Pinecone's existing serverless on-demand model, offering enterprises provisioned hardware for steady high query volumes without the variability inherent in usage-based pricing.
Artificial intelligence
#rag
more#rag
Artificial intelligence
fromComputerWeekly.com
6 months ago

Cloudian launches object storage AI platform at corporate LLM | Computer Weekly

Cloudian's Hyperscale AI Data Platform provides on-premise S3 storage plus Nvidia GPUs and RAG architecture to enable secure, rapid natural-language querying of corporate data.
Artificial intelligence
fromInfoWorld
6 months ago

Do vector-native databases beat add-ons for AI applications?

Vector-native databases deliver superior semantic, high-speed retrieval for AI use cases like RAG compared with merely adding vector types to traditional databases.
Artificial intelligence
fromSilicon Canals
8 months ago

VectorTree receives EU grant to build Advanced Vector Database for AI

VectorTree's Advanced Vector Database project receives EU funding to enhance AI systems by processing unstructured data and improving similarity searches.
fromHackernoon
6 years ago

How I Super-Charged My LangChain-MySQL Agent: Part 2 | HackerNoon

Contextualizing database schemas into a vector format reduces the complexity for LLM-based retrieval while simultaneously addressing the common rate limit issues with OpenAI APIs.
Artificial intelligence
[ Load more ]