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Not yet.



As I understood this article, they're not even trying to. Their version of understanding isn't of the right sort.


I haven't heard of an AI system understanding that yet but it's a fairly common concept in everyday life for instance dogs tend to have masters. Anyone trying to make an AI understand everyday life or literature is going to have to deal with that.


I think the article speaks to this very point. The people "trying to make an AI understand" are not making it "understand" in the sense that you and I use most commonly use the term.


You're exactly right. If you look closely, present day A.I is modeled after the cortex. It's akin to cutting out the neo-cortex, wiring in i/o hooks, and reprogramming it to one's needs (weak A.I).

The cortical regions are good at creating hierarchical feature maps and we had a bunch of search algorithms laying around in the parts bin. Presto : Present day A.I.

This approach meshes well with 'big-data' companies in possession of large compute stacks and data-sets. So, its the direction things went.

A perfect opportunity for disruption.. The current wave is on borrowed time.




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