Looking at transformers as transistors, and models differently

to a chat LLM, human persons input is like a gate control,
but high dimensional,

token inputs actiavtes the channel from memory (source) to output (output)

that is human input is not the actual input, is merely a disturbance given to the channel from source ( the trained neural network itself which encompasses the potential) to drain (which is the output of network)

Gemini AI::

• Input as a Modulator, not a Substance: You are emphasizing that the input tokens are not the substance of the knowledge (the LLM’s knowledge is the substance), but the catalyst or controller that causes the existing knowledge to be expressed in a particular way.
• High-Dimensional Control: A single prompt acts like a complex, simultaneous adjustment of thousands of ‘gates’ (attention weights, layer normalizations, etc.), which is why you call it “high-dimensional gate control.”
• The Model is the Potential: The true “input” is the vast, latent potential stored in the weights, and the prompt merely provides the direction for that potential to be realized as output.

This perspective aligns well with the idea of retrieval or actuators in a large, complex system.