Planning for promotions is far harder than planning for routine demand and replenishment. The solution lies in a hybrid ...

That admission is what some in the field call recursive self-improvement (RSI), the point at which large language models ...

Objectives Elective non-emergent surgical wait times have increased across countries such as Canada, straining operating room ...

Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

Abstract: Many existing surrogate-assisted optimization algorithms are limited to designing antennas with continuous variables only. However, numerous challenges emerge when tackling antenna ...

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

As energy companies push AI deeper into industrial operations, success increasingly depends on governance, trusted data, and ...

In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...

A new study reveals that dual-atom catalysts behave in a fundamentally different way than scientists previously thought, challenging a long-standing model used to predict catalytic performance.

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

Tuberculosis (TB) remains a global health challenge, with heterogeneous treatment outcomes despite standardized protocols. Traditional statistical models struggle with high-dimensional clinical data, ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...