low resource translation is definitely still bad, you're right.
> near perfect translation just by putting each word through a dictionary, and the neural networks can disambiguate things and smooth over the problems in the output
Funnily enough, this is not a terrible explanation of how the current sort of approaches to low-resource MT work.
> low resource translation is definitely still bad, you're right.
No, you've misunderstood. Languages that are closely related to each other are fairly easy to translate between. Languages that aren't related are not, regardless of whether you have a large corpus to work with. English - Mandarin is not an example of "low resource translation".
The size of the corpus makes a huge difference. I don't see how can both be true that a. there is this massive failure of translation engines on these language pairs,
b. human translators were unable to differentiate between human translated chinese-english sentences and machine translated sentences.
It's not incredible - but it's also not awful or unusable.
If your use case is (1) being vocally excited about machine translation, or (2) having fun in your spare time, then machine translation is good enough for you.
If you have a genuine need to know what something in a foreign language says, machine translation is unusable.
This isn't really a good usability profile.