Have you ever faced the daunting task of identifying and prioritizing risks in a project, only to feel overwhelmed by the sheer complexity of it all? Whether you’re managing a multi-million-dollar ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

It turns out that matrix multiplication in JAX is not precise by default. Neural networks in flax get around this by writing their own wrapper around the underlying matrix multiplication function.

Abstract: While the Karatsuba algorithm reduces the complexity of large integer multiplication, the extra additions required minimize its benefits for smaller integers of more commonly-used bitwidths.

I have investigated the symptoms of this in some detail but have not tried to find the cause: In short it seems like matrix multiplications with largeish numbers fails inconsistently in windows, and ...

Researchers claim to have developed a new way to run AI language models more efficiently by eliminating matrix multiplication from the process. This fundamentally redesigns neural network operations ...