Google recently updated their translation tool so that it can now translate between language pairs that it hadn't seen before, something they're calling "zero-shot translation." See here for the full paper and here for a summary.
For example, they can train a neural network to translate from Japanese to English and from English to Korean. They then ask it to perform Japanese-Korean translations, and it performs "reasonably" well, even though it was never trained to translate that particular language pair.
What stood out to me is the following conclusion from the article:
5.1 Evidence for an Interlingua:
Several trained networks indeed show strong visual evidence of a shared representation. For example, Figure 2 below was produced from a many-to-many model trained on English↔Japanese and English↔Korean. To visualize the model in action we began with a small corpus of 74 triples of semantically identical cross-language phrases. That is, each triple contained phrases in English, Japanese, and Korean with the same underlying meaning.[...] Inspection of these clusters shows that each strand represents a single sentence, and clusters of strands generally represent a set of translations of the same underlying sentence, but with different source and target languages.
In other words, Google was able to group sentences into an underlying geometrical structure, which corresponds to a meta-language, or as the authors say, an interlingua. Some of the popular articles I've read about this are going so far as to say that Google's Neural Network "invented its own language", but I feel that they're just being sensationalist.
My question: Does this evidence for a meta-language or a shared representation underlying all languages support theories like Jerry Fodor's Language of Thought Hypothesis (i.e. Mentalese) or Chomsky's claim of there being a universal grammar?