Your scenario resembles the behavior of artificial neural networks (ANNs),
The phrase "quote after quote, media after media" suggests sequence modeling, where the model captures relationships between points in a sequence (words, clips, references). Transformers are particularly good at this, using attention mechanisms to weigh the importance of different parts of the input.
The "difficult and sometimes opaque" aspect relates to the "black box" nature of deep learning. Although they produce accurate results, their internal mechanisms (how certain parameters lead to a response) are often hard to interpret, even for
The lack of a "common interpreter" suggests a system that doesn't depend on explicit rules or pre-defined linguistic structures but learns implicit patterns from data. exactly how modern AI models like me work-through statistical learning, not rigid linguistic rules. My add on it is essential for neuro-exploited human intelligence 7of9 not savant