RAG

If you’ve been working with modern AI systems — particularly in the realm of Large Language Models (LLMs), image embeddings, or recommendation engines — you’ve probably heard of vector databases. But what are they really? And why is everyone in the ML community suddenly so excited about them? Let me break it down in simple terms, along with how I’ve been exploring them in my own projects. 🔍 The Problem: Why Traditional Databases Fall Short Traditional databases (like PostgreSQL or MongoDB) are great when you’re dealing with exact matches or relational queries: ...

We hear the term knowledge graph everywhere now — from Google Search to enterprise AI to GenAI apps. But what exactly is a knowledge graph, and why is everyone suddenly obsessed with it? In this post, I’ll break down knowledge graphs in plain language: what they are, how they work, and how I use them in my own projects. 🧱 The Basics: What Is a Knowledge Graph? At its core, a knowledge graph is a network of real-world entities (people, places, things) and the relationships between them. It’s how machines can represent, understand, and reason about the world — kind of like a human brain, but for structured data. ...

We’ve all played with ChatGPT, Copilot, or Claude — typing in questions and marveling at their responses. But behind the scenes, there’s a powerful craft at play: prompt engineering. It’s not just about “asking a question.” It’s about how you phrase it, structure it, and guide the model. Prompt engineering is the new programming skill — and it’s transforming how we interact with AI. 🧠 What Is Prompt Engineering? Prompt engineering is the process of designing effective input prompts that guide large language models (LLMs) like GPT-4 to produce accurate, helpful, or creative outputs. ...

Large Language Models (LLMs) like GPT or LLaMA are great at generating text. But there’s a catch: They only know what they were trained on, and that knowledge is frozen at training time. So what happens when you ask them something from after their training cutoff? Or something super niche, like a policy from your internal HR docs? Enter RAG – Retrieval-Augmented Generation. A technique that combines LLMs with a search engine, enabling them to look up facts on the fly. ...