OpenAI claims their AI-generated algorithm can solve certain hard computing problems faster. Mathematicians are organizing an ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

Linear programming (LP) is a mathematical optimization technique used to maximize or minimize a linear objective function subject to a set of linear constraints. The Simplex Method, developed by ...

As the world races to build artificial superintelligence, one maverick bioengineer is testing how much unprogrammed intelligence may already be lurking in our simplest algorithms to determine whether ...

Building a good mathematics test is a surprisingly hard optimization problem. Every item in a test bank carries its own content domain, difficulty level, cognitive demand, and point value, and a ...

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 ...

From powering search engines to securing data and optimizing networks, algorithms underpin nearly every aspect of modern technology. Understanding how efficiently they can solve problems — and where ...

Quantum computing offers the hope of dramatic increases in computational capabilities. That’s the promise of quantum computers that can handle hundreds of thousands or millions of quantum bits or ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...