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THE NEXT DECADE IN AI / GARY MARCUS 

has already been codified; why, for example, make every system learn anew that objects 
continue to exist in space and time even when they are occluded, when that is a 
universal truth? Moreover, as we have seen, eg in the discussion of GPT-2, learning 
from scratch has thus far been unreliable. Without some prior knowledge, such as the 
rudiments of physical and psychological reasoning, almost none of what we might call 
common sense is learned well.  We need some core knowledge in order to direct the rest 
of what we learn. 

The need for a compromise and innovation is again manifest. We patently need systems 
(presumably neurosymbolic hybrids) that can acquire new causal knowledge, but in 
order to acquire that knowledge we likely need more powerful priors than we have used to 
date.
The Next Decade in AI-