Yashraj Tartesyntaxstation.hashnode.dev·Feb 8, 2025Methods to Supercharge Your Real-World RAG Systems—Part 1Introduction In theory, it's easy to roll out a RAG system—hook up a vector database, process documents, embed the data, embed the query, query the vector database, and prompt the LLM. But in reality, transforming a prototype into a high-performance...Retrieval-Augmented Generation (RAG)
HiSEVENforHiSEVENhisevenblog.hashnode.dev·Feb 3, 2025Decoding Intent: The Magic Behind Semantic Product SearchUnlocking the Power of Semantic Product Search in E-Commerce The fast pace of eCommerce saw the introduction of semantic product search to be a game changer in that scene. Unlike an ordinary keyword-based search engine that uses exact terms, semantic...e-commerce
TechKareertechkareer.hashnode.dev·Feb 1, 2025Beyond the Tables: Diving into the World of Vector DatabasesDo traditional databases feel limiting for modern AI-driven use cases? Enter the world of vector databases, where meaning trumps keywords, and similarity is the name of the game. Today, we’re diving deep into this fascinating area, guided by the expe...Databases
Shreyas DhawareforFutureSmart AI Blogblog.futuresmart.ai·Jan 24, 2025Comprehensive guide to Qdrant Vector DB: Installation and SetupIntroduction: In the era of AI-driven applications and unstructured data management, vector databases have become essential tools for enabling semantic search and similarity matching. Qdrant is one such cutting-edge, open-source vector database desig...3 likes·197 readsMastering Qdrant with LangChain: From Setup to Scalable RAG Applicationssemantic search
Johannes VassforCloudflight Engineering Blogengineering.cloudflight.io·Jan 9, 2025Language Bias in Multilingual Semantic Search SystemsIn the fast-changing field of natural language processing (NLP), semantic search has become crucial for applications like chatbots and fact-checkers. This technology can also enhance search engines, allowing users to find relevant information by aski...45 readsnatural language processing
Prachi Jamdadecodessprachi.hashnode.dev·Dec 2, 2024Understanding Vector Embeddings and Vector StoreIn today’s digital age, data is being generated at a high-speed rate. As I write this, new data is being generated across the globe. Each activity, like scrolling reels, browsing products, giving reviews, and liking a post from your favorite influenc...1 like·59 readsAI
Startup Rabbitstartuprabbitblogs.hashnode.dev·Nov 13, 2024Mastering Semantic SEO: A Beginner’s Guide to Improving RankingsThe world of SEO is challenging and ever-evolving, with top rankings requiring rigorous, white-hat practices. Google’s algorithms focus on content relevancy and user experience. Prioritizing search intent helps boost engagement and improves overall s...semantic search
Sammith S Bharadwajsammith.hashnode.dev·Jul 4, 2024Understanding semantic searchIntroduction During my college days, one of the electives I had chosen was algorithms for information retrieval, it was a pretty fun course, learnt about how webpages are ranked while retrieving, cold start problem and how companies like netflix tack...38 readssemantic search
Leandro Martinsleandromartins.hashnode.dev·Jun 6, 2024An Agnostic Approach to LLM, Vector DB, and Embedding for Semantic SearchWith various solution possibilities in the market for LLM and Vector DB, thinking of an approach that can abstract these solutions becomes increasingly important for future maintenance or even solution changes. In this line of thought, the article ai...generative ai
Ambarish Gangulyambarish.hashnode.dev·May 13, 2024Understanding BBC News Q&A with Advanced RAG and Microsoft Phi3In this blog, we would be doing question and answering on a news data feed. The blog has 2 parts Conceptual Implementation details which comes as expected with code as well as the full code link Please feel free to choose both or at lea...2 likes·353 readsadvanced rag