Embeddings

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Scoured 270 posts in 14.6 ms

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

 🔍Information Retrieval  Content type: Blog
elastic.co·

K-Nearest Neighbors (KNN) Algorithm

 🤖Data science  Content type: Blog
medium.com·

aayush4vedi/drift-spark: Spark-native embedding lifecycle- produce, CDC refresh, model-migrate, audit.

 🪟Context Windows  Content type: Code
github.com··Hacker News

What Limits Does Quantization Place on Dense Top-$k$ Retrieval? A Theoretical Study

 🔍Information Retrieval  Content type: Academic
arxiv.org·

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

 🪟Context Windows  Content type: Discussion

Hashtag Jakarta EE #336

 🪟Context Windows
agilejava.eu·

How LLMs Actually Work: A Friendly Map for Humans • oreoro

 💬Natural Language Processing

Quantum computing, agentic AI, and the next infrastructure layer in financial services

 🔍Information Retrieval  Content type: Blog
elastic.co·

Designing Memory for a Minimal Rust Coding Agent, Without a Vector Store

 🪨Obsidian

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

 🪟Context Windows  Content type: Code
github.com··Hacker News

Your UnEmbedding Matrix is Secretly a Feature Lens for Text Embeddings

 🤖LLM  Content type: Academic
arxiv.org·

RohiRIK/OpenLtm: Long-Term Memory plugin for Claude Code — semantic search, context injection, session learning

 🔍Information Retrieval  Content type: Code

STEDiff: Strengthening Text Embedding for Text-to-Image Alignment in Diffusion Model

 🔬Deep Learning  Content type: Academic
arxiv.org·

Elasticsearch simdvec deep-dive: Walking the memory tightrope to 2x better vector throughput

 🔍Information Retrieval  Content type: Blog
elastic.co·

Neo-X7/Neo-AI: A fully offline AI assistant powered by Ollama. Stores and retrieves conversations using SQLite + LanceDB vector search. No cloud. No API keys. Runs entirely on your machine.

 🧠LLM Inference  Content type: Code
github.com··DEV

$k$-Nearest Neighbors in Gromov--Wasserstein Space

 🤖Data science  Content type: Academic
arxiv.org·

Show HN: Incremental RAG ingestion, only changed chunks get re-embedded

 🪟Context Windows  Content type: Code
github.com··Hacker News

Correlation Is Not Enough: Embedding Human Metadata for Individual Causal Discovery

 🕸️Knowledge Graphs  Content type: Academic
arxiv.org·

I built an open-source persistent memory layer for AI coding agents

 🤖LLM  Content type: Code

TEVI: Text-Conditioned Editing of Visual Representations via Sparse Autoencoders for Improved Vision-Language Alignment

 🤖LLM  Content type: Academic
arxiv.org·
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