Meta's work made headlines and raised a possibility once considered pure fantasy: that AI could soon outperform the world's best mathematicians by cracking math's marquee "unsolvable" problems en ...

Determining the least expensive path for a new subway line underneath a metropolis like New York City is a colossal planning challenge—involving thousands of potential routes through hundreds of city ...

Abstract: Influence maximization is one of the important problems in network science, data mining, and social media analysis. It focuses on identifying the most influential individuals (or nodes) in a ...

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...

Google scientists have created a new algorithm that can solve problems on a quantum processor 13,000 times faster than the world's fastest supercomputers. They say it brings us one step closer to ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Using an advanced Monte Carlo method, Caltech researchers found a way to tame the infinite complexity of Feynman diagrams and solve the long-standing polaron problem, unlocking deeper understanding of ...

This article was originally published at The Conversation. The publication contributed the article to Space.com's Expert Voices: Op-Ed & Insights. Professional astronomers don’t make discoveries by ...

Abstract: In social network analysis, the opinion maximization (OM) problem aims to locate several nodes as a seed set, which starts the information propagation and achieves the most positive opinion ...

Health savings accounts have advantages beyond saving for medical expenses Rebecca Rosenberg has 10+ years of experience as a writer and content strategist. She has written dozens of articles on ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...