Though it's not quite ready to usher in the Doolittle future we've all been waiting for, modern AI translation methods are proving more than sufficient in accurately transforming humanity's roughly 6,500 spoken and written communication systems between one another. The problem is that each of these models tends to only do one or two tasks really well — translate and convert text to speech, speech to text or between either of the two sets — so you end up having to smash a bunch of models on top of each other to create the generalized performance seen in the likes of Google Translate or Facebook's myriad language services.