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Neural Networks - How weighing is done

While doing a crash course on Machine Learning and Artificial Intelligence, I stumbled upon a great visualization that eases understanding of how weighing is achieved. I strongly assume this is how it's done in the human brain as well. This link here: http://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle&regDataset=reg-plane&learningRate=0.1&regularizationRate=0&noise=0&networkShape=4,2&seed=0.09359&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false

This link here is a free "Playground" interactive modeling program that let's you play around to get a feel for how a neural network learns. Crucially, it also has the property of weighing, which is highly important in the process. Weighing is depicted as the thickness of the lines.

The crash course can be found here: https://developers.google.com/machine-learning/crash-course

In the context of AI, weighing is done via a "loss function" that depicts how far away a given result is from the desired result. Results that were close to the desired result are being weighed higher, those which do not, are weighed low. By means of iterative approach, the loss is subsequently minimized, until it gets close to the desired result.

In the context of the psychological system, what kind of technique would it use? "Loss function" makes sense, but loss of what? What would be a "desired" result?

In light of the suggested framework of Defense Mechanisms, it seems plausible to assume that the aim of all Defense Mechanisms is to support the PU until it has no more use of them. With other words, DMs have the aim to help the PU achieve or maintain high CQs. This function runs parallel to the aim of survival, and also parallel to the aim of minimizing pain. If we look at the entire complex:

 

Mode:                 Survival Mode - Deprivation Mode - Sustainability Mode   -   Growth Mode

Program Type:    Hard Coded     -  Soft Coded       - Adaptability Programs  -  Excelling Programs

Environment:   Harsh Environment    -    Everything in between    -  Benevolent Environment

Relative Priority:         High                 -                 Middle                  -              Low

Typical (expected) Duration:     Very Low         -                 Middle                 -              Very High

 

It is obvious that survival has the highest priority, yet, a look at the modes shows that the DM is equipped for every eventuality. It actually has some programs that it runs while defense is not needed. The idea that programs that run under growth mode are designed to run for a long time, speaks to the purpose of the entire system. From a spiritual perspective, it makes lots of sense to assume that the PU has been designed to achieve ascension as fast and as safe as it can. Furthermore, once ascension is achieved, the PU feels perfectly fine in that scenario. The PU is fine-tuned to be in the "ascended" state.

In this context, the "loss-function" that the DMs relate to when deciding how to dispatch the weights is the probability with which CQ remains high. Obviously, if the PU dies, game over. Thus, that specific purpose of the DMs has a very high priority. Otherwise, pain is minimizing the CQ. Thus, that's next on the list. Deprivation is problematic, too, so DMs enhance certain abilities of PU in order to meet its needs, which ultimately allows for higher CQ levels. The less problems the PU has, the more it becomes obvious that the DMs have been serving the purpose of maintaining a high CQ. For when the PU enters growth mode, DMs essentially stop. If the PU leaves growth mode, then DMs activate again.

 

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