Learn what text embeddings are, how they power RAG and semantic search, and how to call embedding APIs from Python using Ollama or an OpenAI-compatible server (for example llama.cpp). Includes persistence, retrieval, and links to chunking, vector stores, and reranking on this site.

#Embeddings #RAG #Python #Ollama #LLM #Self-Hosting #Vector Database

https://www.glukhov.org/rag/embeddings/

Step-by-step RAG tutorial: build retrieval-augmented generation systems with vector databases, hybrid search, reranking, and web search. Architecture, implementation, and production best practices.

#AI #LLM #RAG #Embeddings #Reranking #Vector Database

https://www.glukhov.org/rag/

Big update to Embeddings Playground! You no longer need to enter an API key when you want to play with commercial models from OpenAI, Mistral, or Google.

Try it here:
https://embeddings.svana.name/

#nlp #ml #ai #embeddings #llm #openai

TIL: truncating note bodies to 300 characters and front-loading #embeddings with structured metadata (title, tags, wiki-links) pushed my #obsidian vault recommender’s recall up significantly. The frontmatter I was already including in each note turned out to be the highest-signal input for the embedding model.

https://anoliphantneverforgets.com/til/2026-03-24-shorter-embedding-body-improves-recall

Forscher der Harvard University präsentieren ein Framework, das die Homogenisierung in KI-Modellen verhindert. Durch Eingriffe in die Embeddings beim Fine-Tuning wird eine breitere mathematische Suche erzwungen. Die Methode bewahrt das Reasoning der Systeme und erhöht die Rate der Halluzinationen nicht.

#HarvardUniversity #KünstlicheIntelligenz #Embeddings #OpenSource #News
https://www.all-ai.de/news/beitrage2026/harvard-studie-kreativitaet

Decided to rewrite the backend of my Embeddings playground ... in Rust. I work in Python all the time at my job, and I'm getting a bit bored with it. So, in my side projects, I want to explore other languages and technologies.

#rust #python #machinelearning #embeddings

A full day building a production-grade RAG system.🚀

This #ArcofAI workshop with Wesley Reisz covers ingestion, transcription,
embeddings, vector search, orchestration with Step Functions, and MCP
integration.

https://www.arcofai.com/speaker/7d1e0ac0820b49f0ac378365a185de1c

🎟️ Get tickets: https://arcofai.com

#AI #RAG #VectorSearch #Embeddings #GenAI #AgenticAI #AustinTech #Austin #Developer #AIEngineering

Как я учил компьютер понимать 122 000 фотографий — и почему сложностью оказались не нейронки, а слова

Я крайне редко на фрилансе получал заказы связанные с DS/ML, специалистов для таких задач обычно ищут не там. Причины разные: они требуют долгой интеграции, заказчик сам не понимает задачу, DS более конфиденциален, DS часто возникают внутри продукта, да и в последнее время этот сегмент на фрилансе съедается при помощи LLM: AI integration, RAG боты например. Но, внезапно, мне в личку постучались с таким проектом.

https://habr.com/ru/articles/1010932/

#computer_vision #machine_learning #clip #embeddings #классификация_изображений #zeroshot_learning #уменьшение_размерности_данных #фриланс #продуктовая_разработка #onnx

It's becoming more and more common for agents to skip embedding search entirely. It seems like they do just fine with grep, find and other command-line tools!

How is that possible? Is an agent equipped with a few keyword-search tools really able to outperform a vector DB?

Let's find out.

https://www.zansara.dev/posts/2026-03-15-vector-dbs-vs-grep/

#AI #AIAgents #Embeddings