Fuzzy optimisation has emerged as a vital framework for addressing decision-making and extremum problems where data ambiguity and uncertainty preclude the direct application of classical optimisation ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

By leveraging inference-time scaling and a novel "reflection" mechanism, ALE-Agent solves the context-drift problems that ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

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 ...

We might be witnessing the start of a new computing era where AI, cloud and quantum begin to converge in ways that redefine ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...

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 ...

London, June 5, 2024 – Quantum infrastructure software company Q-CTRL today announced published results that the company says demonstrate a boost of more than 4X in the size of an optimization problem ...

Artificial intelligence has captured headlines recently for its rapidly growing energy demands, and particularly the surging ...

Alessio Figalli studies optimal transport, a field of math that ranges from the movements of clouds to the workings of chatbots. By Siobhan Roberts The words “optimal” and “optimize” derive from the ...