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> Accelerate numerical linear algebra calculations.

Like compute eigenvalues/eigenvectors of large matrices, compute SVDs, solve large sparse systems of equations, etc?

Nothing that fancy. Usually matrix-matrix and matrix-scalar multiplication.

This is indeed the bread-and-butter, but there is use of all sorts of standard linear algebra algorithms. You can check various xla-related (accelerated linear algebra) folders in tensorflow or torch folders in pytorch to see the list of what is used [1],[2]

[1] https://github.com/tensorflow/tensorflow/tree/8d9b35f442045b...

[2] https://github.com/pytorch/pytorch/blob/6e3e3dd477e0fb9768ee...

But is this used for AI or is this "what can we do with an AI chip since we happen to have one anyway?"

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