Tensor networks enable researchers to tackle quantum physics problems previously thought to be solvable only by quantum computers. Credit: Lucy Reading-Ikkanda/Simons Foundation By applying a 1980s ...

AMD's MEXT acquisition is an efficiency upgrade for data centers, not a disruption to the AI memory market.

Crystal Carter and Jen Cornwell tackled AI search from opposite angles at SMX Advanced. Together, they reveal why most ...

Abstract: Robust multiobjective optimization problems (RMOPs) widely exist in real-world applications, which introduce a variety of uncertainty in optimization models. While some evolutionary ...

In 2022, global production of construction materials accounted for more than 7% of total carbon emissions. But how many of ...

Why do algorithms keep showing us content we claim not to want? The answer isn’t manipulation—it’s conflict between our ...

Abstract: This paper proposes a multi-strategy seeker optimization algorithm (MSSOA) for optimization constrained engineering problems. In this paper, three strategies were adopted to improve the poor ...

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 ...

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 ...

This paper introduces a novel meta-heuristic algorithm named Rhinopithecus Swarm Optimization (RSO) to address optimization problems, particularly those involving high dimensions. The proposed ...