Using linear algebra, there exist algorithms that achieve better complexity than the naive O(n3). Solvay Strassen algorithm achieves a complexity of O(n2.807) by reducing the number of multiplications required for each 2×2 sub-matrix from 8 to 7.
The fastest known matrix multiplication algorithm is Coppersmith-Winograd algorithm with a complexity of O(n2.3737). Unless the matrix is huge, these algorithms do not result in a vast difference in computation time. In practice, it is easier and faster to use parallel algorithms for matrix multiplication.