GloVe learns word vectors from how often words appear near other words.
GloVe is like watching the school cafeteria for a month. Words with the same lunch crowd get seats near each other.
It makes fixed word embeddings. People use them for search. They also help sort text and match meanings.
Embedding
GloVe's main output is a word embedding a computer can compare.
Word2Vec
GloVe and Word2Vec are both classic fixed word embedding methods.
Dist. Semantics
GloVe turns the idea of learning meaning from word neighbors into a trainable method.
Matrix Factorization
GloVe is basically factorizing a table of word co-occurrences.