A language learning system that pays attention -- more efficiently than ever before

Human language can be inefficient. Just two words, "language" and "inefficient," convey almost the entire meaning of the sentence. When coded into a broader NLP algorithm, the attention mechanism homes in on key words rather than treating every word with equal importance. That yields better results in NLP tasks like detecting positive or negative sentiment or predicting which words should come next in a sentence. The attention mechanism's accuracy often comes at the expense of speed and computing power, however.