Solving complex optimization problems is central to many modern technologies, from logistics and financial modeling to chip ...

USC is celebrating America's 250th anniversary with animated digital stamps honoring unsung heroes of computing. These stamps ...

An amazing, almost paradoxical picture is unfolding in the stock market. Outwardly, the indices are doing perfectly fine. But ...

In an increasingly AI-gated legal services market, smart law firms—and their legal marketing teams—won’t rely on inbound ...

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 ...

The technology uses predictive algorithms to identify frequently accessed data and move it between flash storage and high-speed memory in real time, reducing the amount of expensive DRAM a data center ...

Your conversion data doesn't just power reporting. It shapes who Google targets, how much it bids, and where your budget goes. We’ve all seen dashboards that don’t make sense when you look into the ...

Arbor separates strategy from execution using isolated git worktrees, so engineering teams can finally trace which optimization actually moved the needle.

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 ...

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