In this video, we delve into the fascinating world of big number multiplication and explore how computers perform this task ...

We further showcase the flexibility of AlphaTensor through different use-cases: algorithms with state-of-the-art complexity for structured matrix multiplication and improved practical efficiency by ...

A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...

By transforming operands into a Montgomery domain, these algorithms enable efficient modular multiplication and exponentiation, which are crucial for public-key cryptosystems.

To multiply two numbers by hand takes a few steps but it's something we're taught in school. When dealing with big numbers, really big numbers, we need to a quicker way to do things.

Completing the tensor decomposition not only allows the AI system to win the game, but also generates a new matrix multiplication algorithm in the process.

These algorithms are significant because they can solve the noncommutative weighted Edmonds' problem in polynomial time, demonstrating that certain complex problems can be tackled efficiently [2].

Computer Scientists Discover Limits of Major Research Algorithm The most widely used technique for finding the largest or smallest values of a math function turns out to be a fundamentally difficult ...