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 ...

Computer scientists have discovered a new way to multiply large matrices faster by eliminating a previously unknown inefficiency, leading to the largest improvement in matrix multiplication efficiency ...

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 ...

The challenge of speeding up AI systems typically means adding more processing elements and pruning the algorithms, but those approaches aren’t the only path forward. Almost all commercial machine ...

Python is convenient and flexible, yet notably slower than other languages for raw computational speed. The Python ecosystem has compensated with tools that make crunching numbers at scale in Python ...

We have said it before, and we will say it again right here: If you can make a matrix math engine that runs the PyTorch framework and the Llama large language model, both of which are open source and ...

[1] A. Melman (2023): “Matrices whose eigenvalues are those of a quadratic matrix polynomial”, Linear Algebra and its Applications, 676, 131—149. [2] A. Melman (2022): “Rootfinding techniques that ...

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 ...