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

LLM Capabilities, t2i generation via inference and resonance inside vector DB of the model is what makes images as this possible. Via : Midjourney

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

🚀 Hiring for V.I.O.N.A. Project — 2 Critical Roles Open 1️⃣ LLM Engineer / AI Systems Developer Looking for someone strong in: Python REST API development Vector Databases (Pinecone / Weaviate / Chroma etc.) Prompt Engineering Token Optimizati

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

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.

other startups face problems like not getting vc not getting funding pre seed and I'm facing problems like not getting full stack developer who can do react frontend backend database server all these things if I find frontend developer then didn't ge

🚨 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

Most people don't even know these basics of RAG. I've explained it in a simple way below. 1. 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴 Convert documents into a format that AI can quickly search later. Step-by-step: • 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁: You start with files like PDFs, Word

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