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🔍 𝟯 𝗞𝗲𝘆 𝗖𝗵𝗮𝗻𝗴𝗲𝘀 𝗧𝗵𝗮𝘁 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗱 𝗟𝗟𝗠 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 & 𝗥𝗲𝗱𝘂𝗰𝗲𝗱 𝗛𝗮𝗹𝗹𝘂𝗰𝗶𝗻𝗮𝘁𝗶𝗼𝗻𝘀 𝗶𝗻 𝗢𝘂𝗿 𝗔𝗜 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁 While solo-building Zinkmail — my AI assistant that cleans up inboxes and surfaces w

SLM vs LLM — which AI model is best for you? I’ve explained both in simple steps below. 𝗦𝗟𝗠 (𝗦𝗺𝗮𝗹𝗹 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹) (𝘴𝘵𝘦𝘱-𝘣𝘺-𝘴𝘵𝘦𝘱) Lightweight AI models built for speed, focus, and on-device execution. 1. 𝗗𝗲𝗳𝗶𝗻𝗲

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

Get RAG-ready data from any unstructured document. This is crazy for AI companies. I've explained below. 𝗦𝘁𝗲𝗽 1 – 𝗨𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝘀 (𝗧𝗵𝗲 𝗦𝗼𝘂𝗿𝗰𝗲) • Real-world PDFs and documents are messy. Tables, images, signa

Day 2 of learning AI/ML as a beginner. Topic: text preprocessing (tokenization) in NLP. I have moved further and decided to learn about Natural Language Process(NLP) which is used especially for translations, chatbots, and help them to generate hum

OpenAI is about to launch a new AI model called Strawberry in the next two weeks. But here’s the twist: it’s designed to enhance reasoning capabilities. Unlike most conversational AIs that instantly spit out answers, Strawberry will actually "thin

The Hidden SEO Benefits of Blogging About Jewelry Trends & Festivals Want to grow your jewelry brand’s visibility on Google? Blogging about jewelry trends and seasonal festivals can deliver big SEO wins. Here’s how: 💎 Ranks for seasonal keywords –

Quietly SEO is evolving are we noticing it? In my opinion, Search engines are no longer how it used to be. That’s not necessarily a bad thing though. With the emergence of tools like Google Gemini and other LLMs, the way users interact with search