[ilaksh]

I think getting near human level for NLP understanding means be being able to visualize and combine all of the dynamic systems that language represents. I mean it's obvious that you can get pretty far just by processing a lot of text, but there is a limit. Some information about the way things work just is not encoded very well in text the way it is in video input. So you need to be able to do a sort of physics simulation for starters. Except it can't just be physics, because there are a lot of patterns that occur that you need to be able to call up and manipulate or combine that are not just plain physics. These patterns are not represented in text.

There are projects doing video and text understanding. I think the trick to efficient generalization is to have the representations properly factored out somehow. Maybe things like capsule networks will help. Although that my guess is that to get really sort of componentized efficient understanding neural networks are not going to be the most effective way.