Nearly all big science, machine learning, neural network, and machine vision applications employ algorithms that involve large matrix-matrix multiplication. But multiplying large matrices pushes the ...

Optical computing uses photons instead of electrons to perform computations, which can significantly increase the speed and energy efficiency of computations by overcoming the inherent limitations of ...

Multiplying the content of two x-y matrices together for screen rendering and AI processing. Matrix multiplication provides a series of fast multiply and add operations in parallel, and it is built ...

New lower values for p get discovered all the time (maybe once a year). It is conjectured that they will approach 2.0 without ever getting quite to it. Somehow Quanta Mag heard about the new result ...

Current custom AI hardware devices are built around super-efficient, high performance matrix multiplication. This category of accelerators includes the host of AI chip startups and defines what more ...

Inverting a matrix is one of the most common tasks in data science and machine learning. In this article I explain why inverting a matrix is very difficult and present code that you can use as-is, or ...