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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

𝗧𝗵𝗲 𝟱 𝗔𝗜 𝗺𝗼𝗱𝗲𝗹𝘀 𝘁𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘀𝘁𝘂𝗰𝗸 𝘄𝗶𝘁𝗵 𝗺𝗲 𝗿𝗶𝗴𝗵𝘁 𝗮𝗳𝘁𝗲𝗿 𝗹𝗮𝘂𝗻𝗰𝗵 (𝗻𝗼𝘁 “𝗯𝗲𝘀𝘁,” 𝗷𝘂𝘀𝘁 𝘂𝗻𝗳𝗼𝗿𝗴𝗲𝘁𝘁𝗮𝗯𝗹𝗲): • Claude 3.5 Sonnet – balanced, smooth, felt almost human. • o3 – search + s

Most of us rely on prompting to get the work done through ChatGPT. Even I used to follow this technique until one of my friends taught me how to master Context Engineering. Here's how it works: Prompting vs Context Engineering Prompting is about a

Same Performance as Claude Sonnet 4 next to Kimi K2 Qwen3-Coder is simply one of the best coding model we've ever seen. → Still 100% open source → Up to 1M context window 🔥 → 35B active parameters They're releasing CLI tool as well ↓

Here's a short roadmap for learning CSS: 1. Basic CSS: Start with understanding selectors, properties, and values to style HTML elements. 2. Box Model: Learn how the box model works, including margin, padding, border, and content. 3. Layout: Dive

Meta has released Llama 3.1, the first frontier-level open source AI model, with features such as expanded context length to 128K, support for eight languages, and the introduction of Llama 3.1 405B. The model offers flexibility and control, enabli

Researchers at Google DeepMind introduced Semantica, an image-conditioned diffusion model capable of generating images based on the semantics of a conditioning image. The paper explores adapting image generative models to different datasets. Instea

We developed a deep neural network for forecasting internal resource demand across systems, expecting it to outperform traditional models. But in deployment, a simple linear regression delivered better accuracy, stability, and faster inference times.

Simple explanation of Traditional RAG vs Agentic RAG vs MCP. 1. 𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗥𝗔𝗚 (𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹-𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻) • 𝗦𝘁𝗲𝗽 1: 𝗨𝘀𝗲𝗿 𝗮𝘀𝗸𝘀 𝗮 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻. Example: “𝘞𝘩𝘢𝘵 𝘪𝘴 𝘵𝘩𝘦 𝘤𝘢𝘱𝘪�

Highlights of OPEN AI's Spring update. They are introducing GPT-4o and the highlights are ●Memory and Context The model now includes a "Memory" feature that recalls previous interactions and context, resulting in a more consistent and tailored use