A new paper in the Quarterly Journal of Economics shows customer service workers using artificial intelligence assistance become more productive and work faster. The effects vary significantly, however. Less experienced and lower-skilled employees improve both the speed and quality of their work, while the most experienced and highest-skilled workers see small gains in speed and small declines in quality. The researchers also found that AI assistance can help worker learning and improve English fluency, particularly for international workers.

Those receiving care then wore a GPS-based device (resembling a smartwatch) that also had an S.O.S. emergency calling function. Their caregivers downloaded a smartphone application that informed them of the location of their care recipient, set physical boundaries that triggered smartphone notifications when crossed and enabled immediate communication with care recipients who wandered.

Texas A&M researchers are developing a hybrid biomechanical physics-informed machine learning model. Their approach combines experimentally measured bone deformation data with governing physics and a robust machine learning framework, enabling precise, personalized predictions of mechanical stress in the bone. This innovation provides an efficient tool for patient-specific dental surgery planning, optimizing bone healing and ensuring long-term implant success.

MIT researchers developed an automated system to help programmers increase the efficiency of their deep learning algorithms by simultaneously leveraging two types of redundancy in complex data structures: sparsity and symmetry.