IBM Watson is a hodgepodge of single-purpose systems inelegantly grafted onto 
the original single-purpose system. The impedance mismatch between parts 
strongly limits its capabilities. Some kinds of elementary reasoning are still 
beyond it because it crosses too many system boundaries.

Interestingly, many years ago (I want to say 2007) it was shown that this 
problem of universalizing reasoning expressiveness in AI systems is the same 
computer science problem as universalizing indexed access in database engines. 
In the specific case of Watson, they are literally the same problem. On the 
upside, it does give you some idea of how data would need to be organized in an 
AGI because progress is slowly being made on the latter topic.

-jar


> On Jul 10, 2015, at 6:25 AM, [email protected] wrote:
> 
> Sounds a bit AGI like:
>  
> [quote]
> However, although the results produced by deep learning systems are often 
> spectacular, the systems responsible are extremely specialized, and they can 
> fail in surprising ways because they don’t comprehend the world in a very 
> meaningful way. If deep learning can be combined with other AI techniques 
> effectively, that could produce more rounded, useful systems.
> Combining disparate strands of AI research could become an important trend in 
> coming years.
> 
> “A key challenge for modern AI is putting back together a field that has 
> almost splintered among these methodologies,”
> 
> [/quote]
> 
>  
> http://www.technologyreview.com/news/539226/ibm-pushes-deep-learning-with-a-watson-upgrade/
>  
> <http://www.technologyreview.com/news/539226/ibm-pushes-deep-learning-with-a-watson-upgrade/>
>  
> AGI | Archives <https://www.listbox.com/member/archive/303/=now>  
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