Nothing can move totally analogue because you cannot infinately half the distance of a movement. So the smallest particle cannot move half the distance of the aether, else the aether would need another aether, and that is a Paradox. So there are tiny steps to everything in the physical universe. Some particles have to be totally reconstructed at a distance.ataxas wrote:Either I am still not understanding your meaning correctly, or you are mistaken. Neural networks, even at their humble beginnings, used much more complex internal variables than "Yes" "No" "Maybe" and back-propagation rules to modify the connection weights between nodes.Pincho Paxton wrote:I was talking about the first Neural Networks which used Yes/No/Maybe as the rules. The computer programes that were taught to speak in English.
Here is a link for the reference of others, who may not be entirely familiar with the debate: http://en.wikipedia.org/wiki/Artificial_neural_network - A link showing neural nets as they are today.
http://en.wikipedia.org/wiki/Feedforward_neural_network - A link showing the simplest and earliest neural net, the single-layer perceptron, and the second generation, a multilayer perceptron, which is the first type to use back-propagation techniques.
The second link, I think, clearly shows that the earliest type of neural net uses analogue internal values (decimal points between -1 and 1), and that it was not used to model English, as, in the 1950s when it was devised, there was no hardware capable of supporting such a function.
In double-checking my information, I had the thought that you might be referring to the first real-world application of a neural network. It was a project named MADALINE, which is still in use, filtering static out of phone lines.
https://www.thedacs.com/techs/neural/ - A link to an article about the history of neural networks, containing information about MADALINE. The history of neural nets is in part 3.0; the link will not link directly.
I then set about searching for the model to which you refer, which seems to be this model:
http://www.springerlink.com/content/n09gg0v2x5736887/ - A summary of the paper in question.
The paper was published in 1994, and submitted in 1993, almost a half-century after the first physically constructed model of a neural net. It is disquieting to accuse another of intellectual dishonesty, and so I will assume that you were convinced of the accuracy of your information, and so did not check your facts.
I wonder what you mean by electrons being analogue. Do you mean their movement? What do you mean when you speak of "aether"? Something like this?:Pincho Paxton wrote:Biological brain is sentient, and you will not find the sentience, but you might be able to use it some day. Sentience is most likely analogue, electrons could be analogue, but I would say that the move through a aether, and that would make them work in steps, although, very, very tiny steps, totally indivisable.
http://scienceworld.wolfram.com/physics/Ether.html
Then, do you deny the existence of vacuums?
I deffinately deny the existence of vacuums, impossible to see through space in a vacuum. The photons would fly apart in every direction. So the Moon would just scatter all over the place into a mist. Colours would also be impossible, and waves would never propogate. Nothing would be able to move without an Aether, because nothing would be there to pass the message of movement along.
I never knew about other neural networks before the one that I mentioned which was shown on TV. But during that program they said that this was the first Neural Network to be modelled from the human brain, and that the scientists were surprised that three simple rules like YES/NO/MAYBE would actually work like a human brain. I think it was Horizon.The paper was published in 1994, and submitted in 1993, almost a half-century after the first physically constructed model of a neural net. It is disquieting to accuse another of intellectual dishonesty, and so I will assume that you were convinced of the accuracy of your information, and so did not check your facts.