The BBC (Prime) is running a very interesting series since yesterday. It's called "The Human Mind" and explains a lot of the issues that I was talking about in this blog over the last few weeks.
Whereas academic institutions mostly work within certain academic constraints, you need to come up with proof of certain findings or intuitions and validate your imagined model against current knowledge. Sometimes you invalidate existing knowledge, most of the times it more or less falls into place or enriches it.
Some great inventions or innovations come from people that had a desire to do certain things. The invention of the airplane, the invention of electricity. But electricity probably wasn't invented within the big picture of having electricity at every house. And probably neither was the telephone. At some point, it's just pure curiosity that drives a great invention, which is just used and exploited later (MS invented Web2.0 through the XMLHttpRequest object, but only some years later was it used widely in browsers. Now many sites popped up that constantly use it).
Can one design without imagination?
Imagination being visualization, proto-typing in your head. Design is then not just coming up with the idea, but making it clearer and clearer until you have it ready to be written on paper. Then the skills of course to visualize it properly on paper or in digital form.
If one were to re-design a very complex piece of work, say, the human brain, then you can't really do that unless you have an imagined idea of how it should work. Most of previous work available deals with Artificial Intelligence, which you could also call "pattern recognition".
In some other comments, I stated that the brain may be this big pattern recognition machine, but it still doesn't explain the kind of signal that flows through the brain. But maybe the signal itself is not that important (that is, there might not be meaning in the signal), but maybe the triggering of that signal through its amplitude and its length is.
Most of science is finite. This is to give us certain limitations and scope of reasoning. Wherever we encounter something that is not finite enough, we have quite severe difficulty in toying with it or imagining the little things that it is composed of. So breaking things apart in smaller chunks, whether functional or through other categorizations, helps to solve the eventual problem. Subdividing it into chunks that different experts treat differently also helps (like building an airplane).
As with previous posts, I think linear memory is the wrong kind of model for artificial intelligent machines. Maybe radial memory would work or spherical memory, where symbols are aligned close to one another and where travelling away from the center might induce some kind of special meaning (so that travelling "through" that memory from one part to another somehow might be steered by thought).
So, that is the essence of today. In order to come up with some kind of redesign in computers that at some point in time might match the human brain (or part of it), I'll comply with the following rules:
I should first imagine how it works down to a certain level of detail.
The energy equation should more or less hold.
(that is, the computer should not consume more energy than the human brain on a daily basis).
New tool in town: KnowledgeGenes.com
7 years ago