Last month, OpenAI announced that its latest version of ChatGPT had solved a major math problem, one that had stumped experts ...

In October 2024 I attended a workshop at Harvard University where mathematicians talked through the uses of artificial intelligence in their field. Most were less worried about the future of math than ...

Quantum annealing emerges as a promising approach for tackling complex scheduling problems such as the resource-constrained project scheduling problem (RCPSP). This study represents the first ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Nowadays, frontiers among different sciences are revealed as diffuse, and as a ...

Many complex data analysis problems within and beyond the scientific domain involve discovering graphical structures and functional relationships within data. Nonlinear variance decomposition with ...

In today’s fast-paced, data-driven world, the role of a data analyst has become more crucial than ever. Organizations across industries rely on these professionals to make sense of the vast amounts of ...

Linear programming (LP) is often used within diet optimization to find, from a set of available food commodities, the most affordable diet that meets the nutritional requirements of an individual or ...

Data-driven approaches are becoming increasingly common as problem-solving tools in many areas of science and technology. In most cases, machine learning models are the key component of these ...

To program complex behavior in environments incompatible with electronic controllers such as within bioreactors or engineered cells, we turn to chemical information processors. While chemical ...

After 44 years, there’s finally a better way to find approximate solutions to the notoriously difficult traveling salesperson problem. When Nathan Klein started graduate school two years ago, his ...