MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

Picture a robot capable of changing its shape on demand, squishing, bending, or stretching to perform various tasks like navigating tight spaces or retrieving objects. While this may sound like ...

Machine-learning models can make mistakes and be difficult to use, so scientists have developed explanation methods to help users understand when and how they should trust a model's predictions. These ...