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I have always wondered about this question i.e. is it always necessary to model our systems "exactly" on the natural physiology? Case in point, men, inspired from the flights of the bird in nature first tried to build the flying machines using "flaps". Soon, though, it became apparent that flight is best achieved via a circular motion instead of the flaps. Similar arguments for wheels and automobiles that roll instead of emulating a walk.

What I'm saying is, maybe the neurons and the human intelligence are indeed order of magnitudes more complex than our current research. But maybe, our simple designs will prove more efficient and equally effective in the long run? To be clear, this is of course not to imply that we have nothing to gain from a deeper understanding of the human physiology. It's just a curious question of mine.

4 comments

There are a whole lot of problems where if you/the system, dont have time, resources, information etc reaching an optima isnt possible. With sucb problems striving for efficiency turns out to be a negative. See the explore-exploit trade off for example.

So finding simple efficient solutions are never enough. We have to study other mechanisms. Especially the brain.

When you dont have an explanation, people make up stories. And the made up stories effect everything.

Here is Richard Gariott, game designer, explaining how quickly it happens - "if we put a fishing pole there, it had to do something, so we made fish for players to catch. This wasn’t meant to be a key feature of the game, and we didn’t spend a lot of time on it, stocking the water with generic-looking fish. We gave fishermen a simple fifty-fifty chance of catching a fish every time they put their line in the water. It didn’t matter if they were fishing in a river or in the ocean, there was a fifty-fifty chance. It didn’t matter if it was morning, noon, or night, still fifty-fifty. But to our surprise, when we launched the game, fishing immediately became very popular. Fifty-fifty doesn’t mean the result will alternate each time, it means that over a span of time the result will be even. As a consequence players began to speculate that there might be some other rule behind fishing, believing that they had better results when fishing two or three yards farther offshore than when they cast close to the riverbank. Fishing at night, some people were convinced, was more productive than fishing in the afternoon. People created their own mythology; they believed there were special fishing holes, and wouldn’t tell anyone else where they were. None of that was true, but players believed it"

Samething happens with people and the stories they tell about their brains and the thoughts that come out of it. See Xi Jinping for example. What his brain is doing effects billions of people.

But tomorrow someone might stumble upon rules underlying it all and that will have huge effects on existing stories we tell ourselves.

What I like about the flying analogy is that we are not optimising for the same scenarios. You have birds flying 10 000 - 20 000 miles without having to go to external shops for service, needing replacement parts and being very energy efficient. Our simpler models optimize for specific scenarios like specific routes with this much fuel and optimizing for specific total cost. I guess your example with neural networks would be AI classifying pictures better than humans which is very specific and I guess achievable with our primitive models.

This is an excellent response! I’d also add that the things we can optimize for are very limited—for both flight and AI—by the current state of materials science.

Bird wing mechanics are incredibly complex, and we’re still learning how far that extends. This video[0] shows how the feathers are spread apart and turned to decrease drag on the upstroke, something that we probably couldn’t see before slow-motion video was invented. Even though we know now, we cannot (to my knowledge) create artificial feathers with the same properties as real ones, nor can we build the biomimicry required to make use of them. (Plus, nobody wants to be in a bouncing bird-wing body even for a short flight.)

[0] https://youtu.be/4jKokxPRtck

We understand translation without studying legs or wings. We don't understand what intelligence is. Studying existing systems may help.

> is it always necessary to model our systems "exactly" on the natural physiology

To replicate their effects? Probably not. "Probably" because it could very well be that evolution came up with something that anything more straightforward simply can't replicate, or maybe can replicate but not economically.

But to understand what already exists, I think yes, you do need to be able to model it. Otherwise the speed with which you acquire your understanding becomes glacial because all of your means of acquiring new knowledge are slow, low in scale, and destructive.