Aniket HinganeAdvanced Multi-Stage, Multi-Vector Querying Using the ColBERT Approach in QdrantSmart Retrieval → Brilliant Answering → Elevating AI PerformanceJul 301Jul 301
Han HELOIR, Ph.D. ☕️inTowards Data ScienceThe Art of Chunking: Boosting AI Performance in RAG ArchitecturesThe Key to Effective AI-Driven RetrievalAug 1813Aug 1813
Yann-Aël Le BorgneinTowards Data ScienceOpenAI vs Open-Source Multilingual Embedding ModelsChoosing the model that works best for your dataFeb 2414Feb 2414
Manas ChopraAudio Similarity Search Using QdrantUnlocking the Secrets of Spotify’s Recommendation MagicJun 22Jun 22
Nicola ProcopioQdrant Hybrid Search under the hood using HaystackGentle Introduction to Hybrid SearchJun 62Jun 62
DatadriftersLlama 3 Powered Voice Assistant: Integrating Local RAG with Qdrant, Whisper, and LangChainVoice-enabled AI applications will forever change how we interact with technology.May 174May 174
Srijanie Dey, PhDinTowards Data ScienceDeep Dive into Vector Databases by Hand ✍︎Explore what exactly happens behind-the-scenes in Vector DatabasesMar 205Mar 205
Tomaz BratanicinNeo4j Developer BlogGraph-based Metadata Filtering for Improving Vector Search in RAG ApplicationsOptimizing vector retrieval with advanced graph-based metadata techniques using LangChain and Neo4j.Apr 291Apr 291
Rayyan ShaikhQdrant — Using FastEmbed for Rapid Embedding Generation: A Benchmark and GuideUnderstanding Embeddings and Their Significance particularly in applications involving natural language processing (NLP) and computer…Jan 163Jan 163
Plaban NayakBuild an Advanced Reranking-RAG System Using Llama-Index, Llama 3 and QdrantIntroductionApr 303Apr 303
Dean AllemangLLMs and Knowledge — the study continuesWe’ve been seeing a lot of folks writing about Knowledge Graphs and LLMs (Large Language Models); I got a list of links from my colleague…Apr 15Apr 15
Maurício MaiaUnderstanding PostgreSQL pgvector Indexing with IVFFlatIn this tutorial, we will discuss how to optimize PostgreSQL’s pgvector with IVFFlat indexing. We’ll cover the following topics:Mar 31, 2023Mar 31, 2023
Jatin TyagiinPython in Plain EnglishBuilding Large Scale RAG Applications — Using Llama-2-13B and QdrantIntroductionMar 191Mar 191
Cameron R. Wolfe, Ph.D.inTowards Data ScienceThe Basics of AI-Powered (Vector) SearchHow the modern AI boom has completely revolutionized search applications…Mar 182Mar 182
Matthias PlaueinMAPEGY TechLLMs for innovation and technology intelligence: news categorization and trend signal detectionIn applications of business intelligence, news articles are an important source for relevant and timely information.Jun 6, 20231Jun 6, 20231
Salvatore RaieliinLevel Up CodingCosine Similarity and Embeddings Are Still in Love?Cosine similarity is the most used method, but it is really the best?Mar 145Mar 145
Pavan BelagattiinLevel Up CodingVector Embeddings Explained for Developers!The world of AI has come a long way. From initial hype to becoming a reality with tools like ChatGPT, it is an insanely amazing time for us…Mar 12Mar 12
QwakIntegrating Vector Databases with LLMs: A Hands-On GuideDiscover how to boost LLMs using vector databases for precise, context-aware AI solutions. Learn to build smarter bots…Feb 296Feb 296
Rayyan ShaikhBuilding Personalized Recommender Systems with Qdrant: A Comprehensive GuideIn the current AI ecosystem, personalized recommender systems play a pivotal role in enhancing user experience.Nov 27, 20231Nov 27, 20231
