And all these are just a few examples of a quickly growing field. It is too early to 
handicap winners, but there are plenty of first steps towards building architectures that 
combine the strengths of the symbolic approaches with insights from machine learning, 
in order to develop better techniques for extracting and generalizing abstract 
knowledge from large, often noisy data sets.   

 

 

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THE NEXT DECADE IN AI / GARY MARCUS 

2.1.3. Common objections to hybrid models and symbol-manipulation 

Despite the growing interest and multiple considerations in favor of investigating 
hybrid models, antipathy to symbol-manipulation looms large in some quarters of the 
machine learning community. As mentioned earlier, Geoffrey Hinton, for example, has 
argued that European investment into hybrid models would be a "huge mistake", and 
likened the study of hybrid models to the use of obsolete gasoline engines in the era of 
electric cars.
The Next Decade in AI-