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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

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

Fine-tune vs Prompt vs Context Engineering. Simple step-by-step breakdown for each approach. 𝗙𝗶𝗻𝗲-𝗧𝘂𝗻𝗶𝗻𝗴 (𝗠𝗼𝗱𝗲𝗹-𝗟𝗲𝘃𝗲𝗹 𝗖𝘂𝘀𝘁𝗼𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻) 𝗙𝗹𝗼𝘄: 1. Collect Data → Gather domain-specific info (e.g., legal docs). 2. Sta

Why Every Jewelry Brand Needs Professional Photography in 2025 In 2025, great jewellery isn't enough—how you present it matters more than ever. With shoppers making split-second decisions online, professional photography is no longer a luxury. It’s a

"A Survey on Post-Training of Large Language Models" This paper systematically categorizes post-training into five major paradigms: 1. Fine-Tuning 2. Alignment 3. Reasoning Enhancement 4. Efficiency Optimization 5. Integration & Adaptation 1️⃣ Fin