[wyldfire]

I have no idea if these concepts are similar, but as a machine learning beginner, I found the concept of a "perceptron" [1] to be useful in understanding how networks get trained. IIRC a perceptron can be activated or not activated by a particular input depending on the specific network-under-training between the two. What it means to be activated or not depends on that perceptron's overall function. That perceptron is like a single "cell" of the larger matrix, maybe like the cells in your brain.

When I read the GP description referring to "embedding" above I thought of the perceptron.

Definitely not supernatural at all. The act of making an automaton that "can perceive" feels to me like it's closer to the opposite. Taking that which might seem mystical and breaking it down into something predictable and reproducible.

[1] https://en.wikipedia.org/wiki/Perceptron