Why Transformers Need Positional Encoding For Time Series: A Visual Guide

# Why Time-Series AI Models Need to Know Where They Are in a Sequence AI models that predict trends in data over time (like stock prices or weather) can struggle because they process information in parallel rather than reading it step-by-step like humans do—so they need a special technique to remember *when* each piece of data occurred relative to others. Think of it like adding timestamps to out-of-order emails so the AI understands the sequence; without this "positional encoding," the model treats today's data the same as last month's data.