When identical charges repel each other but are confined to the surface of a sphere, they seek the arrangement with the lowest possible energy. The idea is simple, but the problem gets harder to solve ...

Since you last thought about math, the people who think about math every day have been freaking out. A month ago, when OpenAI announced that one of its powerful internal models had cracked a ...

After a previous solution angered mathematicians, the company characterized the new release as being more responsive to concerns about A.I. disrupting research. By Kenneth Chang and Siobhan Roberts ...

OpenAI on Tuesday said its artificial intelligence technology has cracked one of the Millennium Problems –– seven famously difficult and unsolved questions in mathematics that have stumped even the ...

Read about how mathematicians are dealing with the AI takeover of their field in our newest feature here. For the second time ever, someone has solved one of the seven Millennium Prize Problems—math’s ...

“If you are a mathematician,” one of the world’s leading mathematicians recently wrote, “you may want to make sure you are sitting down before reading further.” And you’ll definitely need to sit down ...

Penn researchers have developed a smarter AI method for solving notoriously difficult inverse equations, which help scientists uncover hidden causes behind observable effects. By introducing ...

Multi-agent task allocation plays a crucial role in achieving efficient collaboration in heterogeneous multi-agent systems, especially in complex and dynamic environments. However, existing ...

St. John's University fired its basketball program's general manager, Matt Abdelmassih, this week. He was reportedly managing a $10 million roster. St. John's University spent $10 million on its ...

The original version of this story appeared in Quanta Magazine. In 1939, upon arriving late to his statistics course at UC Berkeley, George Dantzig—a first-year graduate student—copied two problems ...

Abstract: This article proposes an expectation maximization sample transfer identification (EM-STI) algorithm to address the parameter identification problem in dynamic systems with nonideal data.