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It is so subtle I've never quite grasped it. 'Endowing machines with common sense and deep understanding' in the obvious way was tried for 50 years (it's the obvious thing to try first) and didn't work. What's different about your proposal now? (ps. I'll read the book...)
Yes, please read the book. But also compare the argument you just made - “it’s already been tried, and failed” — to what might have been applied to deep learning in 2010.
From what I've read in recent critiques of DL, the arguments for "more than statistical analyses/pattern recognition" also tend to simply point at what DL can't do (yet). Is there something in your book that *doesn't* point out DL failures, and is different from F+P 1988?
inter alia, we examine in unprecedented depth what the problems for DL are, focusing on two detailed case studies, AND we also subject *symbolic approaches* to considerable scrutiny, & then make specific proposals about what problems in common sense have highest priority.
I haven't read Gary's book yet, but I doubt he's advocating 'endowing machines with common sense' (his words) 'in the obvious way was tried for 50 years' (Felix's words)
I'm inclined to agree that a focus on 'common sense and deep understanding' is the right approach. But I suspect it can be done with deep learning and the right architecture
That's a fair riposte! I suppose we must both agree that the best approach is not to do *exactly* what was done previously again - that's why I'm interested in your (book's) proposal for what to do differently.
indeed the book is an effort to learn from history in order to glean insight into what might next be tried
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