[fdej]

What makes you say that? I've had good speedups with Strassen multiplication in variable precision (or with floating-point, in case you meant fixed-point arithmetic).

[SuchAnonMuchWow]

Strassen method is faster than native multiplication, but it is not stable: you will get much larger rounding errors when implementing it using floating point numbers, compared to native multipllication. And fine precision is required for a lot of algorithm implemented using matrix multiplication, such as matrix inversion or gradient descent, so this is often a problem.

[dnautics]

do we know if the rounding errors are a big deal for numerical methods that can tolerate inaccuracy (like gradient descent for machine learning)?

[jl2718]

Speed is fine. The issue is numerical stability.

[fdej]

Yes, indeed, and Strassen is a bad default algorithm because of this. There are specialized situations where the numerical stability isn't an issue though.