Mastodawn

📚 Kilo Code Series #5: Codebase Indexing with Nomic & Qdrant!

Enable semantic AI search across your entire codebase.

📖 Read: https://devopstales.github.io/ai/kilo-code-series-05-indexing/?utm_source=twitter&utm_medium=social

Kilo Code: Codebase Indexing with Nomic and Qdrant

In our previous post, we explored the different modes of Kilo Code. While these modes are powerful, their effectiveness depends on the quality of the context they can access.

DevOpsTales

sayzard Mar 19

AA (@measure_plan)

사진 검색·뷰잉 실험: threejs 인터페이스 위에 smolVLM + Roboflow RF-DETR 기반 컴퓨터 비전과 ChromaDB 시맨틱 검색을 결합해, 도시·색상·객체 같은 자연어로 전체 사진 라이브러리를 검색할 수 있게 구성한 사례를 공유함.

https://x.com/measure_plan/status/2034272042158108907

#threejs #smolvlm #roboflow #chromadb #semanticsearch

AA (@measure_plan) on X

exploring new ways to search and view my photos • threejs interface • smolVLM + roboflow RF-DETR computer vision • chromaDB semantic search this lets me use natural language search (city, color, object) across all my photos

X (formerly Twitter)

sayzard Mar 14

Engadget (@engadget)

Nothing이 자사 AI 앱을 업데이트하여 시맨틱 검색 기능을 도입하고 이벤트 추적을 위한 새로운 방식을 추가했습니다. 사용자가 의미 기반 검색으로 더 정교한 검색이 가능해지고, 이벤트 트래킹 방법도 개선되어 앱 내 데이터 탐색 및 추적 경험이 향상됩니다.

https://x.com/engadget/status/2032553912717193594

#nothing #ai #semanticsearch #eventtracking

Engadget (@engadget) on X

Nothing updates its AI app with semantic search and a new way to track events https://t.co/ysFN6DwHr2

X (formerly Twitter)

sayzard Mar 3

Github Awesome (@GithubAwesome)

Context+라는 MCP 서버가 발표되었습니다. Tree-sitter 기반 AST 파싱과 Spectral Clustering을 결합해 대규모 코드베이스를 의미론적으로 색인·검색 가능한 형태로 변환함으로써, AI 에이전트의 토큰 소모와 컨텍스트 손실 문제를 완화하고 대규모 엔지니어링에서의 검색·추론 효율을 높이는 개발자용 인텔리전스 솔루션입니다.

https://x.com/GithubAwesome/status/2028811480108261523

#codeintel #treesitter #semanticsearch #mcp #aiagents

Github Awesome (@GithubAwesome) on X

Are you tired of your AI agent burning through tokens and losing context? Context+ is an MCP server that acts as semantic intelligence for large-scale engineering. By combining Tree-sitter AST parsing with Spectral Clustering, it turns your massive codebase into a searchable,

X (formerly Twitter)

pgEdge Postgres Mar 3

pg_semantic_cache: an open-source extension that enables semantic query result caching in #PostgreSQL. Traditional caching requires exact query matches; this extension uses vector embeddings to find and retrieve cached results for semantically similar queries.

✨ Give the project a try on GitHub (and don't forget to star the project while you're there): https://github.com/pgEdge/pg_semantic_cache

#postgres #data #llm #semanticsearch #ai #aiengineering #opensourceai #opensource

GitHub - pgEdge/pg_semantic_cache

Contribute to pgEdge/pg_semantic_cache development by creating an account on GitHub.

GitHub

Brandon H

Feb 26

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…

Vector Data in .NET - Building Blocks for AI Part 2 - .NET Blog

Explore the power of Vector Data in .NET AI for enhancing semantic searches and intelligent applications.

.NET Blog

pgEdge Postgres Feb 23

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

GitHub - pgEdge/pgedge-vectorizer: A PostgreSQL extension to create chunk tables for existing text data, and populate them with embeddings using your favourite LLM.

A PostgreSQL extension to create chunk tables for existing text data, and populate them with embeddings using your favourite LLM. - pgEdge/pgedge-vectorizer

GitHub

sayzard Feb 19

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

ITmedia AI＋ (@itm_aiplus) on X

“あいまい”検索システム「SoftMatcha 2」　東大や京大、Sakana AIなどが開発　巨大化するAI学習データを高速検索 https://t.co/yOV58YpYgx

X (formerly Twitter)

Specbee Feb 13

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

OpenSearch Project Feb 9

🔍 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

Revolutionizing enterprise search: OpenSearch Vector Engine unleashed

Discover how OpenSearch Vector Engine transforms enterprise search with AI-powered semantic capabilities, hybrid search, and RAG integration for superior accuracy and relevance.

OpenSearch