"My favorite Gary Marcus quote", via Geoffrey Hinton:) http://www.cs.toronto.edu/~hinton/marcusquote.html …
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I am not nearly knowledgeable enough to comment on this. But I remember the argument being that while machine translation & language seem to be tasks better suited for symbolic AI, feature representations from DL without an explicit understanding of tasks still do well on them
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machine translation and even Superglue are poor proxies for genuine comprehension the fact that large datasets have correlations with things doesn’t mean models like BERT can comprehend a narrative, medical report, or news article
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An example: AI translator can correlate "I see what you mean" and "I understand what you mean". However, the act of understanding is not known to the machine. As there is no prior than the experience itself, machine will stop where the experience starts.
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