Mathematical modelling and optimisation in packing problems constitute a critical research area that combines advanced algorithms, rigorous analytical formulations, and practical applications. This ...

The Covid-19 pandemic has triggered a wave of severe economic disruption around the world, causing widespread chaos, profound changes in the business landscape and overwhelming operational challenges.

The study of the Cahn-Hilliard equation has long provided a robust framework for modelling phase separation in binary mixtures, with applications spanning materials science, tumour growth, and ...

Mathematics, like many other scientific endeavors, is increasingly using artificial intelligence. Of course, math is the ...

There’s a curious contradiction at the heart of today’s most capable AI models that purport to “reason”: They can solve routine math problems with accuracy, yet when faced with formulating deeper ...

A marriage of formal methods and LLMs seeks to harness the strengths of both.

OpenAI’s unreleased model solved five of 10 unpublished research-level math problems and proposed a breakthrough physics formula, signaling a new era for AI in science.

"What's the difference between mathematical optimization and machine learning?" This is a question that — as the CEO of a mathematical optimization software company — I get asked all the time.

They had to throw away most of what it produced but there was gold among the garbage. Google DeepMind has used a large language model to crack a famous unsolved problem in pure mathematics. In a paper ...