| > We should judge approaches to AI based on their results That's why the article discusses examples where currently popular approaches fail. > not on their conformance to a (vague, incorrect, untested) model of human cognition. What model of human cognition is "incorrect"? And is it the one presented by Marcus, or a strawman? > But if you want to genuinely influence the direction of the field, you have to lead by example and produce novel/interesting research results Are you claiming Marcus has produced no interesting research results? > not by kvetching in The New Yorker that your favorite approach is not getting enough attention Why use the term "kvetching"? I'm curious. |
The model of human cognition I'm referring to is the hybrid connectionist-symbolic one that Marcus is well known for advocating (are YOU strawmanning? lol). I'm criticizing it for being more a theoretical model than one grounded in the physical realities of the brain, which of course no one really understands. Proposing a research program on that basis requires a high burden of proof.
> Are you claiming Marcus has produced no interesting research results?
Yes I am claiming that, if the benchmark for "interesting" is deep learning.
There are indeed areas where deep learning is limited, and hybrid approaches could be superior. I would argue that there is not even close to enough evidence that a hybrid approach has improved generalizable power.
> Why use the term "kvetching"? I'm curious.
Huh? I guess it's the term my mother would use.