What is Data Annotation?
An AI model is like a brilliant student that can't see or hear. Raw data--like an image or a sound file--is meaningless to it. **Annotation** is the process of translating that data into a language the AI can understand. It's the act of teaching.
Level 1: Classification
The simplest form of annotation. We give the entire piece of data a single label. We aren't telling the AI *where* the objects are, just *what* the overall scene is about.
Level 2: Object Detection
Now we get more specific. We draw a "bounding box" around each object of interest and give each box its own label. This teaches the AI to not only identify objects, but also to locate them in space.
Level 3: Semantic Segmentation
This is the most precise form of annotation. Instead of a rough box, we "paint" every single pixel of an object with its corresponding label. This gives the AI an incredibly detailed, pixel-perfect understanding of the scene.
Why It's the Most Important Job in AI
Without annotation, training data is just noise. High-quality, accurate annotation is the invisible, human-powered work that makes self-driving cars, medical imaging AI, and every other advanced computer vision system possible.