In most software interviews a decade ago, success hinged on how quickly a candidate could write code on a whiteboard. Today, ...

Abstract: Solving constrained multiobjective optimization problems (CMOPs) is a highly challenging work. Numerous complex nonlinear constraints significantly add to the complexity of CMOPs, resulting ...

What if you could transform your daily workflow in just minutes, unlocking a tool so intuitive it feels like collaborating with a human partner? With ChatGPT 5.1, that’s no longer a distant dream, ...

NVIDIA achieves a 4x faster inference in solving complex math problems using NeMo-Skills, TensorRT-LLM, and ReDrafter, optimizing large language models for efficient scaling. NVIDIA has unveiled a ...

The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get any better. In 1939, upon arriving late to his statistics course at the ...

In a recent study, mathematicians from Freie Universität Berlin have demonstrated that planar tiling, or tessellation, is much more than a way to create a pretty pattern. Consisting of a surface ...

There are more possible NBA schedule combinations than there are atoms in the sun. That’s not hyperbole—it’s the mathematical reality facing anyone trying to arrange 1,230 games across 30 teams over ...

CAMBRIDGE, U.K. – A small Microsoft Research team had lofty goals when it set out four years ago to create an analog optical computer that would use light as a medium for solving complex problems.

What if the toughest problems humanity faces—those that stump our brightest minds and stretch the limits of human ingenuity—could be tackled by a single, purpose-built system? Enter Gemini Deep Think, ...

Abstract: This paper presents a very-large-scale-integration (VLSI)-based multi-run decremental annealing (MRDA) accelerator for solving combinatorial optimization problems (COPs). The proposed Ising ...