Seems like the hyperbolic conclusion to make? The paper doesn't make that claim. Simple ml models can take data and find patterns, like separate red and blue, o

Seems like the hyperbolic conclusion to make? The paper doesn't make that claim. Simple ml models can take data and find patterns, like separate red and blue, or xy coordinates. Those are a small amount of dimensions and easy to reason about. This seems like the model found on its own another dimension to segregate data in deeper layers by generalizing and using context when learning. Its cool it can do that, but it still to me seems like drawing a best fit line just with higher dimensions. I'm sure someone will correct me if they think I am way off.