Word2vec is usually the standard neural word embeddings implementation. There are other algorithms as well such as glove[1], document embeddings[2] and backpropagation based methods[3]. Facebook just came out with a paper recently that beat word2vec as well[4].
Neural word embeddings are a neat way of representing concepts. I see a great future for automated feature engineering with text (joining audio and images) in deep learning.