via @dotnet : Vector Data in .NET – Building Blocks for AI Part 2

https://ift.tt/VtJUvye
#VectorData #NET #AI #BuildingBlocks #SemanticSearch #RAG #Embedding #Embeddings #VectorDatabase #Qdrant #Redis #CosmosDB #SQLServer #PostgreSQL #SQLite #InMemory #VectorSto…

Did you know? Our pgedge-vectorizer tool (on GitHub: https://github.com/pgEdge/pgedge-vectorizer) automatically chunks text content and generates vector embeddings with the help of background workers.

OpenAI, Voyage AI, and Ollama are supported as embedding providers, and a simple SQL interface allows you to enable vectorization on any table. (There’s even built-in views and functions for monitoring queue status.)

#github #opensource #semanticsearch #vector #vectordatabase #openai #ollama #voyageai

ITmedia AI＋ (@itm_aiplus)

'SoftMatcha 2'라는 '애매함(曖昧)' 검색 시스템이 도쿄대, 교토대, Sakana AI 등 공동으로 개발되었으며, 급증하는 AI 학습 데이터에서 유사성 기반 고속 검색을 가능하게 해 학습 데이터 관리·검색 효율을 크게 개선할 수 있다고 보도되었습니다.

https://x.com/itm_aiplus/status/2024319295556374564

#semanticsearch #softmatcha2 #informationretrieval #aidata

Relying on keyword search alone? Read this blog to add semantic search and AI-powered search terminologies to your SEO dictionary to build smarter, modern enterprise websites.

https://www.specbee.com/blogs/semantic-search-vs-keyword-search-difference

#seo #semanticsearch #keywordsearch #relevanceoptimization #aisearch #ai #searchintent

🔍 Modernize Enterprise Search with OpenSearch Vector Engine - Neel Shah

OpenSearch Vector Engine brings semantic, hybrid, and AI-powered search to enterprise data. This guide covers the technical basics, deployment strategies, code snippets, diagrams, and real-world use cases to help you build smarter search systems.

📚 https://opensearch.org/blog/revolutionizing-enterprise-search-opensearch-vector-engine-unleashed/

#OpenSearch #EnterpriseSearch #VectorSearch #SemanticSearch #AI #OpenSource

via @dotnet : .NET AI Essentials – The Core Building Blocks Explained

https://ift.tt/CjSQkpt
#NET #DotNet #CSharp #AI #ArtificialIntelligence #MEAI #MicrosoftExtensionsAI #LLM #SemanticSearch #VectorData #Embeddings #AgentFramework #ModelContextProtocol #MCP #Mi…

I'll be speaking at PHP Tek in May — two talks I've been building toward for a while.

**Kubernetes for PHP Developers**: The translation guide from Docker Compose to production K8s. No 40-hour course required.

**Semantic Search in Laravel**: Building search that understands meaning using pgvector and embeddings. Based on what I built for DailyMedToday.

Both talks from production experience, not theory.

Full details: https://eric.mann.blog/speaking-at-php-tek-2026/

#PHP #Kubernetes #Laravel #PHPTek #SemanticSearch

RAG-системы: что это такое, принципы работы, архитектура и ограничения

Retrieval-Augmented Generation (RAG) всё чаще упоминается в контексте LLM и всё чаще фигурирует в требованиях к разработчикам, но за этим термином обычно скрывается довольно размытое представление о том, как такие системы реально устроены. В этой статье я разбираю RAG как архитектурный подход: зачем он вообще появился, какие задачи решает, как выглядит базовый пайплайн от данных до ответа модели и где на практике чаще всего возникают проблемы.

https://habr.com/ru/articles/989000/

#rag #llm #retrieval #nlp #embeddings #semanticsearch #informationretrieval

🔍 Đã có công cụ CLI mới mang tên **semantica** – tìm file “theo nghĩa” thay vì tên chính xác!
🖥️ Python, dùng FastEmbed để vector hoá và FAISS (sắp chuyển sang usearch) để so sánh độ tương đồng.
⚙️ Chạy hoàn toàn offline trên CPU, không cần API key, biên dịch thành binary độc lập cho Windows & Linux.
💡 Thích hợp cho ai hay quên tên file, muốn tìm tài liệu cũ chỉ bằng mô tả ngắn.

#opensource #cli #semanticsearch #Python #FAISS #Linux #Windows #CôngCụMởNguồn #tìmfile #AI #độnghĩa

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