Ising machines demonstrate significant potential to tackle computationally complex challenges, including combinatorial optimization problems related to logistics, manufacturing, finance, and AI. The ...

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

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 ...

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 ...

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

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

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 ...

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 ...

They are effectively wagering that addressing specific optimization challenges today holds more value than the promise of ...