Before Word2Vec: The Strange, Fascinating Road from Counting Words to Learning Meaning

How NLP kept running into the limits of language - until words stopped being labels and became relations In the first post, we saw how language models turn text into tokens and tokens into numbers. In the second post, we stayed with a deeper question: Once words become numbers, how does meaning not disappear? And in the third post, we entered Word2Vec itself - the moment words stopped being treated merely as labels and began to be treated as positions in a learned relational space.