There has always been a healthy skepticism that deep learning would take us to artificial general intelligence (AGI). But the genuinely amazing things that can be accomplished with the combination of deep learning, big data, and computing power led to a lazy optimism. Fortunately, that is changing, and it is increasingly clear that deep learning alone is insufficient to accomplish much of what is expected. Gary Marcus provides historical and recent context and makes a case for a neurosymbolic hybrid approach. Not too technical.
Content classification and annotation offer useful approaches for content understanding, recognizing whether a piece of content is about a particular topic or mentions a particular entity. But most content exists in a space that is too rich to reduce to classification and annotation. A document is more than a category and a bag of entities. For content understanding to be worthy of the name, it needs to embrace the richness of the content it represents… A more granular approach to content understanding focuses on the similarity between documents.
Daniel Tunkelang’s latest post in his series on content understanding techniques. A bit technical.
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