So when it comes to measuring the efficiency of a multiplication algorithm, it’s the small multiplications that concern us most. Let’s revisit our example, 25 × 63, with efficiency in mind. In order ...

Today, companies use expensive GPU hardware to boost ... out that AlphaTensor discovers a richer space of matrix multiplication algorithms than previously thought — up to thousands for each ...

When the DeepMind paper came out, Kauers and Moosbauer were in the process of searching for new multiplication algorithms using a conventional computer-aided search. But unlike most such searches, ...

They all rely on matrix multiplication for accurate calculations ... “I believe that in the next few years, many new algorithms for fundamental computational tasks that we use every day will be ...

Thus, many researchers have investigated AMM algorithms, which trade off accuracy of matrix multiplication for speed. The key innovation with MADDNESS is using a pre-processing step to produce ...

Using a neural network called AlphaTensor ... When the player manages to do so, this results in a provably correct matrix multiplication algorithm for any pair of matrices, and its efficiency ...

New Linear-complexity Multiplication (L-Mul) algorithm claims it can reduce energy costs by 95% for element-wise tensor multiplications and 80% for dot products in large language models. It maintains ...

finding the theoretically fastest matrix multiplication algorithm. This use of AI to design algorithms demonstrates the potential of the technology for other mathematical discoveries, as well as ...