Word2Vec Explained: The Moment Words Became Relations

How models first learned meaning from context - and why that changed everything In the first post, we built the base layer: Text → Tokens → Numbers → (lots of math) → Tokens → Text In the second post, we stayed with the deeper question: Once words become numbers, how does meaning not disappear? We saw that the answer is not “because numbers are magical.” The answer is this: the numbers are learned in a space that preserves relationships. That was the real story of embeddings. Now we are ready for the next step.