AI scenario planning doesn’t attempt to be “right” in the traditional forecasting sense. Its real value lies in systematic ...

What appears as model bias is often a system-level issue. This phenomenon, known as AI bias propagation, is increasingly becoming a critical concern for enterprises scaling AI across products, ...

Editor's note: The SCM thesis Buffer or Suffer: Dynamic Multi-Echelon Inventory Optimization in Action was authored by Vi Duong and Nic Holwerda, and supervised by Dr. Eva Ponce (eponce@mit.edu). For ...

To address these shortcomings, we introduce SymPcNSGA-Testing (Symbolic execution, Path clustering and NSGA-II Testing), a ...

Abstract: Wearable robotic exoskeletons are frequently explored for their efficacy in physical rehabilitation and for assistance in daily activities in people with motor disorders, yet relatively few ...

In most boardrooms, the final decision still comes down to a small circle of leaders weighing a narrow set of choices. Yet the problems they face now contain thousands, sometimes millions, of possible ...

Drug discovery has traditionally been a reductive process—narrowing down, filtering out, and optimizing within established constraints. Generative AI turns that on its head. It is an expansive force, ...

Incorporating multiple constraints such as task completion time, UAV payload capacity, and flight range into path optimization algorithms allows for more efficient search patterns.

Abstract: The increasing number of electric vehicles (EVs) means both a challenge and an opportunity for the electric grid. Different charging algorithms have been proposed in the literature to tackle ...

Rethinking Legal Department Efficiency: Strategies for Optimization and Cost Savings The challenge in-house counsel are contending with is how legal departments can transcend traditional models to ...