RAG-Part 2 || Vector databases ||Concept of HNSW and ANN explained with implementation

Brute-force search is a death sentence for your AI. 💀 If you have 10 million documents, comparing your query to every single one takes forever. Most people think RAG is just "faster search," but it’s actually high-dimensional navigation. In Part 2 of our RAG series, we’re opening the "Black Box" of Vector Databases to see how they find answers in milliseconds. [What’s Inside] The Latency War: Why traditional SQL fails at "meaning" and why O(n) search is your enemy. ANN vs. KNN: Breaking down Approximate Nearest Neighbor (and why it’s not an Artificial Neural Network). The Highway Analogy…