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Which is the fastest vector db for production in terms of vector similarity search and retrieval?

🚨 Everyone says "RAG is dead" — but I say: It’s just been badly implemented. I’ve worked on AI systems where Retrieval-Augmented Generation (RAG) either changed the game… or completely flopped. Here’s the hard truth 👇 --- 🤯 Most teams mess up

Day 13 of learning AI/ML as a beginner. Topic: Word Embedding. I have discussed about one hot encoding, Bag of words and TF-IDF in my recent posts. These are the count or frequency tools that are a part of word embedding but before moving forward l

All are concerned about product development, but none about product sales. In Western Market the founders works on pre sales just by creating a video render of the product and test the product-market-fit. Anyone who knows about pre sales text me.

💡 5 Things You Need to Master for learn for integrating AI into your project 1️⃣ Retrieval-Augmented Generation (RAG): Combine search with AI for precise and context-aware outputs. 2️⃣ Vector Databases: Learn how to store and query embeddings for e

I'm working towards building India's first Vector DB and Memory Management System. I'm not yet funded by any VC - bootstrapping everything with a very small team. I need the support of the community to take India's deep-tech products to the Global s

🚀 Excited to share my latest YouTube video! demonstrate how to integrate Microsoft's Semantic Kernel with Qdrant, the open-source vector database, to build an intelligent question-answering system for Wikipedia pages citeturn0search3 In this tu

Text Generation What It Is: Text generation involves using AI models to create humanlike text based on input prompts. How It Works: Models like GPT-3 use Transformer architectures. They’re pre-trained on vast text datasets to learn grammar, conte

The Entrepreneur’s Funding Journey (aka "The Hunger Games: VC Edition") 1. Idea stage: “This is going to revolutionize the world.” 2. Prototype stage: “It almost works. On Tuesdays. If you pray.” 3. Pitch stage: “We’re pre-product, pre-revenue,