Matrix multiplication is at the heart of many machine learning breakthroughs, and it just got faster—twice. Last week, DeepMind announced it discovered a more efficient way to perform matrix ...

Over the last few issues, we've been talking about the math entity called a matrix. I've given examples of how matrices are useful and how matrix algebra can simplify complicated problems. A messy ...

Performing math on multidimensional arrays very efficiently. For example, the Strassen algorithm uses fast matrix math on large matrices. See multidimensional array. THIS DEFINITION IS FOR PERSONAL ...

AI training time is at a point in an exponential where more throughput isn't going to advance functionality much at all. The underlying problem, problem solving by training, is computationally ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Several fields of mathematics have developed in total isolation, using their own 'undecipherable' coded languages. Mathematicians now present 'big algebras,' a two-way mathematical 'dictionary' ...