Hacker News Reader

Comment by agumonkey | Hacker News Reader

I often wonder about the neurology of memory regarding thinking. Often I think intelligence main parameter is size of L0 cache in the brain (sorry for the cheap metaphor). Normal people can solve problem, but it will require dozens of round trip between making up ideas / theories, checking them, pruning what was good or not, inferring new ideas from that. While a smart guy will probably do the same steps.. but in one shot. No pause, no gaps..

View on HN

Speed and space (of course!) help, but with terrible O complexity, it doesn't really matter how much memory you have or how fast you are. The search space gets big too fast.

e.g. changing the question, reasoning by analogy

How do we have insight, a hunch straight to the answer? It seems obvious that it's like DL; socially distributed search across people; trying out different things unconsciously... but the truth is, we don't know how we do it. We're like steam-punks saying it's obviously like a mechanical device, or Edison saying it's obviously like electrical relays. We just think in terms of the tech of the day, and by persona; introspection and observation. It's not science. It's maybe science fiction.

When we understand Strong AI, we will already know.

It's always fun to conceptualize the brain as a computer and reason by analogy (iirc it was a steam engine back in the day). I'm excited to see the next advancement the brain gets compared to.

I've caught myself conparing it to an ANN - though they are really quite dissimilar. But yes, I alos wonder what's next. I think it will build on what we have rather than being entirely new (but that's the kind of opinion that ages badly.)

Pretty sure intelligence comes from the quality of your compiler optimizations. If you compile better subroutines that wastes less effort then you get vastly better results. A normal person might run on python while a genius runs on C, it is the same hardware but one is 100 times faster than the other in many cases.

Also explains why the concept of being smart is so elusive, as these optimizations are hard to reproduce and don't generalize to everything we think about. For example, a genius isn't better than an average person at filling out forms, there you are forced to think using unoptimized paths, you can't run those paths 100 times faster.

I love this comment, but maybe not for the intended reason. Why? Because I immediately wanted to add my two cents - another analogy by way of deep learning - that intelligence is like adding model capacity, like additional conv depth or or additional attention heads. That's fine and all, but then it struck me.

We're one level from popping the top off it all and coming to terms that we've fallen into a trap described by Ludwig Feuerbach.[1] The choice of analogies says just as much about us as they do about the subject.

1. Feuerbach(1881) The Essence of Christianity https://libcom.org/files/The%20Essence%20of%20Christianity.p... (p. 17)

An interesting topic for sure. In terms of mastery / skill building, I'd figure those round trips are crucial for the novice and the master. It's just that the master has enough wisdom / experience in the back pocket to know which paths to branch and bound.

Back burner thought and mind wandering are also really important aspects of intelligence and creativity, but it's difficult to test them.

yes and experience/maturity, which is kinda knowing how to deal with finite immediate memory in the face of larger conceptual and unknown domains.

Reply on news.ycombinator.com