Reminds me of the old line about how, if the brain were so simple we could understand it, we'd be so stupid that we couldn't. Also reminds me of an older book

Reminds me of the old line about how, if the brain were so simple we could understand it, we'd be so stupid that we couldn't. Also reminds me of an older book I read about AI (I think it was On Intelligence by Jeff Hawkins?) where I first became aware of the idea we had been scrambling to create AI without first having a good definition of intelligence or deep understanding of how it works in our own brains. And when I ask myself or other people how they define intelligence, it always comes down to some variation on "the ability to solve problems", which feels deeply beside the point and likely to never produce something that "feels" intelligent. But I don't necessarily agree that there is this special case of human intelligence that makes it impossible to understand or model. I would really like to believe it, personally, because I don't want AGI. I just don't buy that that's the explanation for our failure to do so up to now. It seems like we ought to be able to do it, but that we're muddling in the wrong direction, coming up with an exceptionally clever implementation of an approach which cannot produce intelligence that satisfies our intuition about what intelligence is. To tie it back to the article, I keyed in on the word 'design' in LeCun's statement that, "contrary to what you might hear from some people, we do not have a design for an intelligent system that would reach human intelligence." In other words, that it's not just a quantitative difference (more parameters, more data) but that a different approach than what we are taking would be necessary.