#semanticsearch — Public Fediverse posts

via @dotnet : Microsoft Agent Framework – Building Blocks for AI Part 3

https://ift.tt/CQUJ8zm
#MicrosoftAgentFramework #AIAgent #BuildingBlocksForAI #MEAI #MicrosoftExtensionsForAI #VectorData #RAG #SemanticSearch #AIinDotNet #AgentFramework #AIContextProvider …

I spent some time trying to make search behavior visible in one small Quarkus app.

Full-text is good at exact terms. Vector search helps when user language and catalog language drift apart. Hybrid is usually the one I’d trust first in a real product search.

This article walks through all three with Quarkus, PostgreSQL, Elasticsearch, Hibernate Search, and local embeddings.

https://www.the-main-thread.com/p/full-text-vector-hybrid-search-quarkus-java

#Java #Quarkus #PostgreSQL #Elasticsearch #SemanticSearch #HibernateSearch #VectorSearch

📚 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

#KiloCode #AI #Indexing #SemanticSearch

📚 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

#KiloCode #AI #Indexing #SemanticSearch

📚 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

#KiloCode #AI #Indexing #SemanticSearch

📚 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

#KiloCode #AI #Indexing #SemanticSearch

📚 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

#KiloCode #AI #Indexing #SemanticSearch

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

➡️ Read more: https://www.pgedge.com/blog/pg_semantic_cache-in-production-tags-eviction-monitoring-and-python-integration

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

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…

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…

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…

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…

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

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

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

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

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

Bạn mệt vì tìm kiếm trên WP trả về kết quả không liên quan? Queryra – API tìm kiếm ngữ nghĩa chỉ học từ dữ liệu của bạn. Sync sản phẩm/bài viết, trả về ID đúng, nhanh <500 ms, miễn phí 100 bản ghi/500 truy vấn/tháng. Plugin WP chỉ cần nhập API Key. #search #semanticsearch #AI #WordPress #WooCommerce #công_nghệ #tìm_kiếm

https://dev.to/gronrafal/i-built-a-search-api-that-actually-understands-your-content-not-the-entire-internet-3474

How small shifts in phrasing reveal whether an agent understands intent or only echoes words. https://hackernoon.com/when-the-words-change-but-the-meaning-shouldnt-paraphrases-as-stress-loads #semanticsearch

Learn to build a local AI semantic search engine with Ollama and TypeScript. No cloud APIs needed—understand intent, not just keywords. Free and
priv https://hackernoon.com/local-ai-powered-search-engine-using-slm-embeddings #semanticsearch

FYI: Semantic Search: Understanding User Intent & Content #shorts: Semantic search moves beyond simple text matching. It's about understanding the relationship between user queries, content, and the domain it exists within, ensuring more relevant search results. #semanticsearch #SEO #contentstrategy #userintent https://www.youtube.com/shorts/kSRILR1R2p0

Searching for Meaning (1 of 2): The Technology Behind Semantic Search timdasey.substack.com/p/searching-fo… (useful explanations) #AI #SemanticSearch

Searching for Meaning (1 of 2)...

via #AIFoundry : Foundry IQ in Microsoft Agent Framework

https://ift.tt/7pPmwX4
#FoundryIQ #MicrosoftAgentFramework #AI #Python #RAG #KnowledgeBase #AzureAI #EnterpriseAI #MultiHopReasoning #SemanticSearch #AIIntegration #OpenSource #IntelligentRetrieval #DataManagement #Clou…

ARBITER: what it is / what it isn’t

IS

semantic scoring
geometric fit
negative answers
offline 26MB

ISN’T

LLM
vector DB
embeddings
retrieval

getarbiter.dev
#AI #NLP #RAG #AIInfra #SemanticSearch

Implementing RAG from scratch with Python, Qdrant, and Docling

https://techlife.blog/posts/implementing-rag-from-scratch-qdrant/

#RAG #VectorSearch #Qdrant #Embeddings #SemanticSearch #LLM #Python

ICYMI: Semantic Search: Understanding User Intent & Content #shorts: Semantic search moves beyond simple text matching. It's about understanding the relationship between user queries, content, and the domain it exists within, ensuring more relevant search results. #semanticsearch #SEO #contentstrategy #userintent https://www.youtube.com/shorts/kSRILR1R2p0

Tìm kiếm tài liệu dễ dàng với DocFinder! ng dụng này sử dụng tìm kiếm ngữ nghĩa để giúp bạn tìm lại tài liệu bị mất trên PC. #DocFinder #TìmKiếmTàiLiệu #SemanticSearch #ngDụngHay #TàiLiệu #DocumentFinder #SearchTool #ProductivityTool

https://www.reddit.com/r/SideProject/comments/1oyyez3/document_finder_docfinder/

🔍 Can AI transform how we discover biological datasets?

🔗 Public Omics Explorer (POE): Enabling integrative semantic search across GEO omics datasets based on PubMed publications. Computational and Structural Biotechnology Journal, DOI: https://doi.org/10.1016/j.csbj.2025.11.004

📚 CSBJ: https://www.csbj.org/

#Bioinformatics #Genomics #SemanticSearch #ArtificialIntelligence #BiomedicalResearch #FAIRData #OpenScience #ComputationalBiology #DataDiscovery #MachineLearning

Semantic Search: Understanding User Intent & Content #shorts: Semantic search moves beyond simple text matching. It's about understanding the relationship between user queries, content, and the domain it exists within, ensuring more relevant search results. #semanticsearch #SEO #contentstrategy #userintent https://www.youtube.com/shorts/kSRILR1R2p0

🤖✨ See AI beyond the hype! Steve Eardley demos LLM-powered semantic search in academic repositories, with live comparisons & insights on AI’s promise & pitfalls. 🌐📚

📄 Abstract: https://doi.org/10.7557/5.8363

#AI #OpenScience #Munin2025 #SemanticSearch #UiT

🤖✨ See AI beyond the hype! Steve Eardley demos LLM-powered semantic search in academic repositories, with live comparisons & insights on AI’s promise & pitfalls. 🌐📚

📄 Abstract: https://doi.org/10.7557/5.8363

#AI #OpenScience #Munin2025 #SemanticSearch #UiT

🤖✨ See AI beyond the hype! Steve Eardley demos LLM-powered semantic search in academic repositories, with live comparisons & insights on AI’s promise & pitfalls. 🌐📚

📄 Abstract: https://doi.org/10.7557/5.8363

#AI #OpenScience #Munin2025 #SemanticSearch #UiT

AI and the Future of Search Engines: What's Next?

https://jivoice.com/future-of-search-engines-ai/

#AIinsearch #largelanguagemodels #GoogleSGE #conversationalsearch #futureofinformationretrieval #semanticsearch #aipoweredsearch #SEOintheageofAI #predictivesearch #generativeAIsearch

via @dotnet : Upgrading to Microsoft Agent Framework in Your .NET AI Chat App

https://ift.tt/JARZoFE
#MicrosoftAgentFramework #DotNet #AIChatApp #AIIntegration #Chatbot #CSharp #VisualStudio #AzureOpenAI #DependencyInjection #Middleware #SemanticSearch #Software…

Semantic Search over the National Gallery of Art

https://nga.demo.mixedbread.com/

#HackerNews #SemanticSearch #NationalGalleryOfArt #ArtTech #Innovation #MuseumExperience

Crypto Storage Gets Smarter as Walrus Adds Zark Lab’s AI Search Layer - TLDR:

Walrus partners with Zark Lab to make uploaded files AI-enriched and instan... - https://blockonomi.com/crypto-storage-gets-smarter-as-walrus-adds-zark-labs-ai-search-layer/ #decentralizedstorage #semanticsearch #technology #blockchain #metadata #zarklab #crypto #walrus #defi #web3 #ai

Crypto Storage Gets Smarter as Walrus Adds Zark Lab’s AI Search Layer - TLDR:

Walrus partners with Zark Lab to make uploaded files AI-enriched and instan... - https://blockonomi.com/crypto-storage-gets-smarter-as-walrus-adds-zark-labs-ai-search-layer/ #decentralizedstorage #semanticsearch #technology #blockchain #metadata #zarklab #crypto #walrus #defi #web3 #ai

Crypto Storage Gets Smarter as Walrus Adds Zark Lab’s AI Search Layer - TLDR:

Walrus partners with Zark Lab to make uploaded files AI-enriched and instan... - https://blockonomi.com/crypto-storage-gets-smarter-as-walrus-adds-zark-labs-ai-search-layer/ #decentralizedstorage #semanticsearch #technology #blockchain #metadata #zarklab #crypto #walrus #defi #web3 #ai

Crypto Storage Gets Smarter as Walrus Adds Zark Lab’s AI Search Layer - TLDR:

Walrus partners with Zark Lab to make uploaded files AI-enriched and instan... - https://blockonomi.com/crypto-storage-gets-smarter-as-walrus-adds-zark-labs-ai-search-layer/ #decentralizedstorage #semanticsearch #technology #blockchain #metadata #zarklab #crypto #walrus #defi #web3 #ai

🚀 NEW on We ❤️ Open Source 🚀

Jessica Garson shares how vector databases go beyond keywords to power semantic search, embeddings & smarter AI workflows. A practical intro to RAG & context-aware apps.

Read the article: https://allthingsopen.org/articles/vector-databases-semantic-search-ai

#WeLoveOpenSource #VectorDatabases #AI #SemanticSearch #MachineLearning #OpenSource

The Case of the Vanishing #Hit Count: Rethinking Query Craftsmanship in a Post-Boolean World— Reflections from Day 2 of my FSCI 2025 workshop on AI‑powered search

👉 Understanding the Shift from Exact #Boolean Hits to the "Top-k" Results of #SemanticSearch and the Evaluated Hits of #DeepSearch.

By Aaron Tay

https://open.substack.com/pub/aarontay/p/the-case-of-the-vanishing-hit-count

#SearchEvolution #AcademicSearchChallenges #Discovery #InformationDiscovery #InformationLiteracy #infolit #TopK #SearchStrategy #booleanoperations #HitCount

The Case of the Vanishing #Hit Count: Rethinking Query Craftsmanship in a Post-Boolean World— Reflections from Day 2 of my FSCI 2025 workshop on AI‑powered search

👉 Understanding the Shift from Exact #Boolean Hits to the "Top-k" Results of #SemanticSearch and the Evaluated Hits of #DeepSearch.

By Aaron Tay

https://open.substack.com/pub/aarontay/p/the-case-of-the-vanishing-hit-count

#SearchEvolution #AcademicSearchChallenges #Discovery #InformationDiscovery #InformationLiteracy #infolit #TopK #SearchStrategy #booleanoperations #HitCount

The Case of the Vanishing #Hit Count: Rethinking Query Craftsmanship in a Post-Boolean World— Reflections from Day 2 of my FSCI 2025 workshop on AI‑powered search

👉 Understanding the Shift from Exact #Boolean Hits to the "Top-k" Results of #SemanticSearch and the Evaluated Hits of #DeepSearch.

By Aaron Tay

https://open.substack.com/pub/aarontay/p/the-case-of-the-vanishing-hit-count

#SearchEvolution #AcademicSearchChallenges #Discovery #InformationDiscovery #InformationLiteracy #infolit #TopK #SearchStrategy #booleanoperations #HitCount

The Case of the Vanishing #Hit Count: Rethinking Query Craftsmanship in a Post-Boolean World— Reflections from Day 2 of my FSCI 2025 workshop on AI‑powered search

👉 Understanding the Shift from Exact #Boolean Hits to the "Top-k" Results of #SemanticSearch and the Evaluated Hits of #DeepSearch.

By Aaron Tay

https://open.substack.com/pub/aarontay/p/the-case-of-the-vanishing-hit-count

#SearchEvolution #AcademicSearchChallenges #Discovery #InformationDiscovery #InformationLiteracy #infolit #TopK #SearchStrategy #booleanoperations #HitCount

The Case of the Vanishing #Hit Count: Rethinking Query Craftsmanship in a Post-Boolean World— Reflections from Day 2 of my FSCI 2025 workshop on AI‑powered search

👉 Understanding the Shift from Exact #Boolean Hits to the "Top-k" Results of #SemanticSearch and the Evaluated Hits of #DeepSearch.

By Aaron Tay

https://open.substack.com/pub/aarontay/p/the-case-of-the-vanishing-hit-count

#SearchEvolution #AcademicSearchChallenges #Discovery #InformationDiscovery #InformationLiteracy #infolit #TopK #SearchStrategy #booleanoperations #HitCount

Aaron Tay: A Deep Dive into EBSCOhost’s Natural Language Search and Web of Science Smart Search – Two bundled “Ai-powered”search (I). “This post will examine EBSCOhost’s Natural Language Search (NLS) and, in the next post, Web of Science’s Smart Search (not to be confused with Web of Science Research Assistant). Both are interesting because they introduce this ‘semantic’ query translation […]

https://rbfirehose.com/2025/07/23/aaron-tay-a-deep-dive-into-ebscohosts-natural-language-search-and-web-of-science-smart-search-two-bundled-ai-poweredsearch-i/

Aaron Tay: A Deep Dive into EBSCOhost’s Natural Language Search and Web of Science Smart Search – Two bundled “Ai-powered”search (I). “This post will examine EBSCOhost’s Natural Language Search (NLS) and, in the next post, Web of Science’s Smart Search (not to be confused with Web of Science Research Assistant). Both are interesting because they introduce this ‘semantic’ query translation […]

https://rbfirehose.com/2025/07/23/aaron-tay-a-deep-dive-into-ebscohosts-natural-language-search-and-web-of-science-smart-search-two-bundled-ai-poweredsearch-i/