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6 Chunking Methods for RAG you should know. I’ve explained it in a simple, step by step way. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴? 1. Chunking means splitting large documents into smaller pieces. 2. Helps LLMs search and understand data better. 3. Essent

6 Chunking Methods for RAG you should know. I’ve explained it in a simple, step by step way. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴? 1. Chunking means splitting large documents into smaller pieces. 2. Helps LLMs search and understand data better. 3. Essent

Google's Gemini app has taken the top spot on the Apple App Store, fueled by its viral Nano Banana AI feature. Nano Banana effortlessly transforms photos into hyper-realistic 3D figurines using simple text prompts. This viral feature has attracte

🚀 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

7 database types used in modern AI systems. I’ve explained each one in simple steps. 1. 𝗩𝗲𝗰𝘁𝗼𝗿 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 • 𝗠𝗮𝗶𝗻 𝗣𝘂𝗿𝗽𝗼𝘀𝗲: Store embeddings so AI can search by meaning. • 𝗛𝗼𝘄 𝗶𝘁 𝘄𝗼𝗿𝗸𝘀: Text/images → vectors → neare

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

Day 25 of learning python as a beginner. Topic: database handling. I used to write simple programs which just showed some text in the console when I started learning python. I didn't used to store that data somewhere because I didn't know how to.

Everything you need to go from 0 to launch: 🔐 Authentication – Powered by Supabase + Auth.js with Magic Links (signup, login, logout) 🗂 Database – MongoDB & Supabase to store all user actions 💸 Payments – Fully integrated with Stripe, LemonSq

Your AI sucks because it’s stuck at Level 1. You can easily take it to Level 3. I've explained below. 𝗦𝘁𝗲𝗽 1 – 𝗕𝗮𝘀𝗶𝗰 𝗟𝗟𝗠 (𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴) • This is the simplest level of AI systems. • You give input text or a docu

Prompt vs Context vs RAG. I've explained it in a simple way below. 1. 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 Prompt Engineering is about 𝗰𝗹𝗲𝗮𝗿 𝗶𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗶𝗼𝗻𝘀, not magic words. • 𝗗𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝗳𝗶𝗻𝗮𝗹 𝗴𝗼𝗮𝗹: What exactly do