Word Embeddings
One-hot encoding a vocabulary treats every word as equally different from every other word — "cat" is exactly as far from "dog" as it is from "bicycle." Word embeddings replace that with geometry: words that appear in similar contexts end up close together in a continuous vector space, and "close" starts to mean "similar" in a way a model can actually use.