I am current working on an algorithm for unsupervised grammar learning. Part of what made me change my mind about this, is that I realized that what is required to learn syntax of language is also what is required to learn semantic relationships between objects, based on this syntactic data. You just have to go up one level of abstraction.

I believe we are not too far from having algorithms, which can parse a natural language sentence into a semantic representation which link abstract concepts in a way that is powerful enough for e.g. question answering beyond just information retrieval (statistical guess work based on word frequencies). I am not so sure how or if we can build this into strong AI, though.