One other benefit of using word2vec-stle training is that you can also control the learning rate, and gracefully handle new training data. SVD must be done at-

One other benefit of using word2vec-stle training is that you can also control the learning rate, and gracefully handle new training data. SVD must be done at-once, and you need to use sparse matrix abstractions for raw word vectors. The implementation and abstractions you use actually make it more complex than word2vec imho. Word2vec can train off pretty much any type of sequence. You can adjust the learning rate on the fly (to emphasize earlier/later events), stop or start incremental training, and with Doc2Vec you can train embeddings for more abstract tokens in a much more straightforward manner (doc ids, user ids, etc.) While word2vec embeddings are not always reproducible, it is much more stable with the addition of new training data. This is key if you want some stability in a production system over time. Also, somebody edited the title of the article, thanks! The original title of "Stop using word2vec" is click-bait FUD rubbish. I think in this case we're trying too hard to wring a good discussion out of a bad article.