4min chapter

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#54 Gary Marcus and Luis Lamb - Neurosymbolic models

Machine Learning Street Talk (MLST)

CHAPTER

Neural Networks and Relational Work in Artificial Intelligence

In the end of the day, a graph can be seen as a relation, right? You can translate graph knowledge or graph neural networks into relational forms. And when one looks at relational reasoning, that is the reasoning and the learning that people are after in AI. Can we ignore symbolic computing in computer science? Absolutely not. Are we going to prove that P equals NP using deep learning techniques? Probably not. We are going to use symbolic machinery. It doesn't make sense to say that symbols are useless because they are not.

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