A $1 million prize awaits anyone who can show where the math of fluid flow breaks down. With specially trained AI systems, ...

Abstract: This article investigates a class of systems of nonlinear equations (SNEs). Three distributed neurodynamic models (DNMs), namely a two-layer model (DNM-I) and two single-layer models (DNM-II ...

One of the fundamental operations in machine learning is computing the inverse of a square matrix. But not all matrices have an inverse. The most common way to check if a matrix has an inverse or not ...

OpenAI said it, too, had built a system that achieved similar results. By Cade Metz Reporting from San Francisco An artificial intelligence system built by Google DeepMind, the tech giant’s primary ...

Abstract: The time-dependent nature of real-world problems and the ubiquity of linear equations underscore the fundamental importance of time-dependent systems of linear equations (TDSLE). However, ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

AlphaEvolve uses large language models to find new algorithms that outperform the best human-made solutions for data center management, chip design, and more. Google DeepMind has once again used large ...

Polynomial equations are a cornerstone of modern science, providing a mathematical basis for celestial mechanics, computer graphics, market growth predictions and much more. But although most high ...

A mathematician has uncovered a way of answering some of algebra's oldest problems. University of New South Wales Honorary Professor Norman Wildberger, has revealed a potentially game-changing ...

A UNSW Sydney mathematician has discovered a new method to tackle algebra's oldest challenge—solving higher polynomial equations. Polynomials are equations involving a variable raised to powers, such ...