This is a good paper for anyone interested in how modern Machine Translation works at the level of detail you might get from a well-written text in a college-level CS course (which is what I believe this is from). The paper starts with a background on statistical machine translation and then goes through the newer approach of sequence-to-sequence learning for translation, including word replacement and attention mechanisms. It's a good overview.

But if you are looking for a higher-level introduction that covers the same big ideas in ~10 minutes for a more general audience, here's my take: https://medium.com/@ageitgey/machine-learning-is-fun-part-5-...