A cool thing about linear models is that they can be used to model non-linear correlations by using transformations. For example, an exponential function can be made linear if you just take the logarithm.
Doesn't have to be 'trivial'. It could be a trillion-parameter MoE LLM spitting out 10,000-large embeddings. But a lot of that will act linearly and can, in theory, be put into your linear model easily & profitably.