Earlier quoted context omitted.
It's learning the meaning of words, and the relationships between them. Word2vec is definitely an impressive algorithm. But at the end of the day, it's just a tool that cranks out a fine-grained clustering of words based on (a proxy measure for) contextual similarity (or rather: an embedding in a high-dimensional space, which implicitly allows the words to be more easily clustered). And yes, some additive relations b…
Word2vec may be crude, but it demonstrates that you can learn non-trivial relationships between words with even such a simple algorithm. What is the meaning of a word, if not the relationship it has to other words? Gender was just an example. There are lots of semantic information learned by word2vec, and the vectors have shown to be useful in text classification and other uses. It can learn subtle stuff, like the re…
There's also the relationship it has with the world.