Tuesday, November 13, 2018

Building Machines That Learn and Think Like People

Cornell University

Specifically, we argue that these machines should (a) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (b) ground learning in intuitive theories of physics and psychology, to support and enrich the knowledge that is learned; and (c) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations.

I would like to see more about each of these topics, but as far as I can see, this is not provided. 

No comments:

Post a Comment