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I'll add to this.

It's not only the boundary that is fractal.

We'll soon see that learning on one dataset (area of fractal) with enough data will generalize to other seemingly unrelated datasets.

There is evidence that the structure neural networks are learning to approximate in a generative fractal of sorts.

Finally, we'll need to adapt gradient descent to operate at move between different scales



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