In context, that claim was an explanation of what I was trying to get at with the phrase "conceptual understanding". We don't have a conceptual understanding of language. We do have a conceptual understanding of how to translate between human languages — Proof: we can translate between human languages. If you think that's not adequate proof then you're disagreeing with me on the semantics of "conceptual understanding". If you have an alternative name for that then I'd appreciate it because I think my usage is confusing.
It's not a useless notion of "conceptual understanding" though, because while being able to have a program complete a task implies having the conceptual understanding necessary for that task, it's possible to have the conceptual understanding but not be able to make a program, if, for instance, it would require greater (within reason) computing resources.
It does sound pretty useless because the same logic can be used to prove that we have a conceptual understanding of general intelligence, because after all we exist and we think.
Re:Artificial Addition (2007)
by lern_too_spel on Monday January 09, 2017 @10:18PM
(#13362275)
Google Translate never used conceptual modeling. The original Google Translate used statistical machine translation.
Google Translate itself may have been done through statistical machine translation, but that wasn't Google's first attempt at the subject.
In particular Google spent around $100 million in 2003 for Applied Semantics, in part hoping that their natural language processing expertise could be used for translation. That technology was superseded by statistical techniques.
Except that we don't. The original Google Translate used the conceptual modeling approach to translation, and it was absolute shit for any non-closely related language pairs. Google Translate (and Baidu, etc.) now uses deep networks whose operations are rather opaque. We don't understand in detail how they work. But that didn't stop us from building them.