I think 4x4 matrices for 3D transforms (esp homogenous coordinates) are very elegant.
I think the intended critique is that the huge n*m matrices used in ML are not elegant - but the point is made poorly by pointing out properties of general matrices.
In ML matrices are just "data", or "weights". There are no interesting properties to these matrices. In a way a Neumann (https://en.wikipedia.org/wiki/Von_Neumann%27s_elephant) Elephant.
Now, this might just be what it is needed for ML to work and deal with messy real world data! But mathematically it is not elegant.
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