Researchers from around the world gathered at Cornell Tech for a workshop exploring how physics-aware artificial intelligence can accelerate the discovery of molecules and materials while improving the reliability of machine learning models.
Middle and high school students from across New York state spent three days discovering potential career paths during the annual 4-H Career Explorations Conference, held June 30 to July 2 at Cornell.
An artificial intelligence system that operates like a collaborative team of medical experts could accelerate clinical trial design, one of the most difficult steps in drug development.
Training artificial intelligence to enforce even seemingly straightforward rules – like balls and strikes in Major League Baseball – is a messy, dynamic process that takes time and careful evaluation of the technology.
A two-semester collaboration between the Cornell AI Innovation Hub, graduate students and the Cornell Treasury Operations team transformed a time‑consuming, manual investigation process into a tool that helps staff process cryptic payments.
For consequential decision-making, the benefits of a simple index score vs. a less-interpretable predictive AI algorithm depend, researchers from Cornell found, on the desired outcome as well as the decision’s intended audience.
