Faster matrix multiplication in general is an important applied topic, because it can speed up all sorts of scientific, engineering, and ML algorithms that have it as a step (often one of the bottleneck steps). However this new technique appears to be more of theoretical interest because of how impossibly large the matrices would have to be before it becomes faster than simpler techniques.
The Strassen algorithm (http://en.wikipedia.org/wiki/Strassen_algorithm) is used in practice though, and is faster than the naive multiplication approach for moderately large matrices, so this kind of research sometimes produces practical speedups. Not in this case without significant further breakthroughs to really bring down the size of matrices that it wins on, though.
The Strassen algorithm (http://en.wikipedia.org/wiki/Strassen_algorithm) is used in practice though, and is faster than the naive multiplication approach for moderately large matrices, so this kind of research sometimes produces practical speedups. Not in this case without significant further breakthroughs to really bring down the size of matrices that it wins on, though.