Vector Similarity

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Scoured 159 posts in 45.0 ms

HNSW vs LSH: How Elasticsearch hits 0.99 recall@10 at 15,000 QPS — and what it costs

 📇Vector Indexing  Content type: Blog
elastic.co·

Understanding HNSW: The Engine Behind Fast Vector Search

 🎯Vector Search
chimchim89.github.io·

A Fun & Absurd Introduction to Vector Databases • Alexander Chatzizacharias

 🎯Vector Search  Content type: Video
youtu.be··r/programming

When More Cores Hurts: The Vector Database Scaling Paradox in HPC

 🎯Vector Search  Content type: Academic
arxiv.org·

a desktop GUI to browse, search, & visualize your vector databases

 🎯Vector Search
vectorlens.dev··Hacker News

MongoDB as a Vector Database for AI Agents-MongoDB

 🎯Vector Search
foojay.io·

Quiz: Embeddings and Vector Databases With ChromaDB

 🎨Chroma
realpython.com·

HelixDB/helix-db: HelixDB is an OLTP graph-vector database built in Rust.

 🎯Vector Search  Content type: Code
github.com··Hacker News

Pinecone vs Qdrant vs Weaviate

 🕸️HNSW  Content type: Blog
rephrase-it.com·

HNSW-MS: Hierarchical Graph Indexing Enables Accurate Real-Time Mass Spectral Similarity Search at Repository Scale

 🎯Qdrant  Content type: Academic
biorxiv.org·

Reinforcement learning in linear embedding space unlocks generalizable control across soft robot configurations

 🧭Content Discovery  Content type: Academic
nature.com·

New comment by yorktanaka2024 in "Ask HN: Who wants to be hired? (June 2026)"

 🔄LLM RAG Pipelines  Content type: Discussion

Rayforce

 🎯Qdrant  Content type: Code

Best practices for building a modern app with vector search

 🏗️Search Infrastructure  Content type: Blog
elastic.co·

LLM-Guided ANN Index Optimization for Human-Object Interaction Retrieval

 🎯Vector Search  Content type: Academic
arxiv.org·

Your AI agent reads the fine print: building a RAG pipeline over EU regulations with Elasticsearch and OGX

 🏗️Search Infrastructure  Content type: Blog
elastic.co·

shoo99/paper-rag: A private, fully-local RAG over your own PDFs: BGE-M3 + embedded Qdrant + a local LLM via Ollama. ~150 lines, nothing leaves your machine.

 🤖AI  Content type: Code
github.com··DEV

Redis for Agent Memory

 🎯Vector Search  Content type: Blog
rephrase-it.com·

Aperon Technical Report: Hierarchical No-Pointer Tangent-Local Search for High-Dimensional Approximate Nearest Neighbors

 🎯Vector Search  Content type: Academic
arxiv.org·

Puffin-Backed Vector Indexes: Attaching Approximate Nearest Neighbor Indexes to Apache Iceberg Snapshots for Compute-Disaggregated Query Engines

 🎯Vector Search  Content type: Academic
arxiv.org·

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