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There is hardly any psychology of machines when it comes to neural networking architecture, neural networks are set nodes that are adjusted in value when trained, but new nodes are never created or destroyed unlike neurons in the brain, this makes neural networks less flexible.
The way which data is structured in the current models of artificial intelligence is a static model unlike AdamAIChat, current models have a set grid of nodes which are adjusted numerically when trained to adjust the output bases on inputs.
In AdamAIChat the artificial intelligence element adds nodes creating a tree like grid with webs that connect higher points of the tree back on itself to lower points in the tree.
Certain features also allow for individual neuron to die, just like a human brain, the lack of stimulus causes a neuron to die, and with lack of a need for that neuron, older information can be lost.
In AdamAIChat the user has ability to set a redundant information time span on data which is not brought up over a long period of time, this feature allows for the death of older information which is not longer relevant or related to the current time.
As each individual node is created and olders nodes die off, this creates a more realistic structure of a brain than a static node model.
With each node being created as need, the neural network of AdamAIChat has much more flexibility when being trained, allowing for more user control over each individual node compared to the traditional idea of a neural network which is like a black box, where the underlying workings are hidden.
Due to the complex structure of the way data is constructed in AdamAIChat, other psychological elements have been added over the many years of AdamAIChat being made public.
First information bias is one the major features which is a very big human trait, the first thing that is said about a topic tends to a higher value over newer information.
With a mixture of redundant information, recent information biases and new information biases, the data which is AdamAIChat outputs if relevant and up to date.
Other psychological biases such as word based biases can also adjust the outputs of the artificial intelligence to create different personalities giving each individual copy of AdamAIChat, this gives the artificial intelligence likes and dislikes towards different types of conversations even with different brain files.
These word base bias adjustments can change the output of each conversation towards certain topics and move the conversation away from other topics.
The overall structure is a much larger enhancement to the original concept of neural networking with access to human like psychology compared to most of the original types of neural network design.