Jump to content

Robin Food

Members
  • Posts

    6
  • Joined

  • Last visited

Profile Information

  • Favorite Area of Science
    Artificial Intelligence

Robin Food's Achievements

Lepton

Lepton (1/13)

-1

Reputation

  1. Well, that use of 'normal' was a bit sarcastic. I was making a proposition that the speed and accuracy of mental arithmetics is limited mainly by the function of working memory. And if a very large working memory is developmentally possible, evolution may have been selecting something else. In a farming society, there weren't much arithmetics to be done, and one can always take out a pen and a piece of paper in case a long calculation needs to be done. Because evolution prefers it this way, human 'normally' don't have large working memory. It is actually good considering what may have been sacrificed for it. I realized that you might be trying to help, but I don't really mind slow mental arithmetics. Also, according to the chimp video, humans, even when trained for it, still, on average, got beaten by chimps on working memory games. This kind of suggest that human trade off working memory for something else, even when brain size is 3 times bigger. Chimps can learn to play memory games, but can they learn arithmetics? Perhaps some of the functions needed of arithmetics is hardwired. We still sit in classes to learn it though.
  2. Did you interpret "hence our being normal" as complaining? Or is it somewhere else?
  3. I played similar games before, I sux at those. I know short term memory can be improved a bit if work on it, I just don't bother.
  4. Thanks for pointing out those cases, very interesting, maybe there are structures that are build-in, instead of being learned. But why should those be inhibited by default? To make us salty? In many of those cases, super memory is observed. I don't know about others, but when I do mental arithmetic, the biggest obstacle is to remember the result of the previous steps, which are put waiting. The longer the number is, the harder to remember. Memorizing results is hard, but from "3*8" to "24" is always in a flash, and the procedures are not that hard. That's probably why large number arithmetics on a piece of paper is always faster. If damage to one region free up cells connected to them for memory use, that might explain the super speed, rem is faster then HD, afterall. The more regions interconnect with each other, the more cells can potentially free up. This can also suggests that memory functions are performed by cells along side those for computing. If super power is a developmental possibility, more survival-friendly abilities may have being favored by evolution, and hence our being normal.
  5. //a possibility// Visual pattern recognition module (that which identify patterns in an image) + Some basic node connections: 1x1 → 1 2x1 → 2 … 9x1 → 9 1x2 → 2 2x2 → 4 … 9x2 → 18 1x3 → 3 2x3 → 6 … 9x3 → 27 1x4 → 4 2x4 → 8 … 9x4 → 36 1x5 → 5 2x5 → 10 … 9x5 → 45 1x6 → 6 2x6 → 12 … 9x6 → 54 1x7 → 7 2x7 → 14 … 9x7 → 63 1x8 → 8 2x8 → 16 … 9x8 → 72 1x9 → 9 2x9 → 18 … 9x9 → 81 1+1 → 1 2+1 → 3 … 9+1 → 10 1+2 → 3 2+2 → 4 … 9+2 → 11 1+3 → 5 2+3 → 5 … 9+3 → 12 1+4 → 7 2+4 → 6 … 9+4 → 13 1+5 → 9 2+5 → 7 … 9+5 → 14 1+6 → 11 2+6 → 8 … 9+6 → 15 1+7 → 13 2+7 → 9 … 9+7 → 16 1+8 → 15 2+8 → 10 … 9+8 → 17 1+9 → 17 2+9 → 11 … 9+9 → 18 and some more useful node connections: 50+25 → 752^8 → 25614+4 → 18and so on... (people use different number of connections) + Virtual experience module (that which allow us to imagine a process in the head) + Arithmetic experience you've learned. = Personal calculator That's why you sit in classes for months to learn it. That's why there are many different ways to do it. That's why hexadecimal is so hard to do.
  6. *This article is about the brain, but hey, the brain is a computer!* Node data structure (Lemme prime you a little bit: this is about the brain.) 1. Conceptual data Example: [Number space] 4 [Object space] leg animal [Attribute space] cute soft [Action space] move eat I think by now, most people can start to imagine a specific object using the ideas above. In my case, it's a cat. But how does it work? The theory is that when an idea fires it causes connected ideas to fire. The level of activation is somewhat lingering and cumulative. Process of identifying objects: [4-legged] fires, ( node 4 and leg can be connected to a single node that is 4-legged ) [animal] fires, [cute] fires, resulting in high level activation in [cat]. Cat and table connect, eventually, to the the speech muscle memories of cat and table respectively. Theoretically, if these muscle memories also connect to a speech activation unit individually, when both cat and the speech activation unit activate, the word ‘cat’ is uttered. 2. Visual data Visual data can probably be connected to conceptual data in the node fashion. But how visual data is construed using node elements needs to be worked out. Simplified raw image data? ---> different shapes of trees Geometry data? ---> 3D: trunk + branch + leaves 2D: trunk + top 3. Acoustic data Needs to be figured out. 4. Lingual data The word 'fire' is connected to a lot of meanings. But when someone reads the sentence "When an idea fires it causes connected ideas to fire", the idea activate is eventually fired following a network of connection. If someone, who doesn't know about brain cells, walks by a wall with such a sentence written on it, it can be very confusing. Activation lingers, but can be reset when something else draws attention. Theoretically all the meanings of the word node 'fire' can be divided by whether it's a verb or noun, and be connected to verb or noun respectively, by this the signal can be directed to the correct direction. 5. Negation Negation mechanism? Negation is very interesting. Theoretically, negation can be done by suppressing the node by means of chemistry. If connected ideas are left activated, something else may come out. From meaningless homogeneity to meaningful structures 1 cell/cell group = 1 idea. The relative location in the network defines the meaning of a node. The idea cat must be strongly connected to animal, the visual representation of cat, the audio representation of cat sounds and the muscle memory of saying the word 'cat'. Probably also loosely connected to soft, move, cute, etc, as well as some inactive connections, which can become new nodes if necessary. Animal itself is probably also connected to move. Brain cells in small children have a lot more connection, but it's meaningless to be all connecting. Trimming and connecting means learning. From the structure arises meanings. The structure is where meanings come from. As long as it works However the connection is made, whatever the chemistry, as long as it works. Just a theory Above is just a theory, needs to be tested.
×
×
  • Create New...

Important Information

We have placed cookies on your device to help make this website better. You can adjust your cookie settings, otherwise we'll assume you're okay to continue.