In 1971, German mathematicians Schönhage and Strassen predicted a faster algorithm for multiplying large numbers, but it remained unproven for decades. Mathematicians from Australia and France have ...

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 ...

In 1971, German mathematicians Schönhage and Strassen predicted a faster algorithm for multiplying large numbers, but it remained unproven for decades. Mathematicians from Australia and France have ...

Researchers at MIT's Computer Science & Artificial Intelligence Lab (CSAIL) have open-sourced Multiply-ADDitioN-lESS (MADDNESS), an algorithm that speeds up machine learning using approximate matrix ...

One of the most fundamental mathematical tools outside of everyday arithmetic has seen its first improvement in 24 years. Although the new method of matrix multiplication, an essential tool for ...

What do encrypted messages, recognizing speech commands and running simulations to predict the weather have in common? They all rely on matrix multiplication for accurate calculations. DeepMind, an ...

The 'algorithm for calculating the matrix product' that AlphaTensor worked on this time is used in various fields related to daily life, such as image processing, game graphics processing, weather ...

Here’s what you’ll learn when you read this story: In 1971, German mathematicians Schönhage and Strassen predicted a faster algorithm for multiplying large numbers, but it remained unproven for ...