Cornell AI News

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.

Internal funding to support social science and humanities research on the societal impacts of AI.
Deadline: August 15, 2026.

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.

Like many other disciplines, AI is moving fast in veterinary medicine and animal health, but the data infrastructure hasn’t kept pace.

Fortunately, Cornell is picking up the slack. The Building Benchmarks for AI-Driven Veterinary Innovation, funded by the Cornell AI Initiative and part of the Thought Summits series, gathered experts across fields to spark solutions in this emerging area.

Cornell computer scientists will lead the development of safety protocols to shore up AI agents and the code they produce.

On May 27, nearly 300 researchers, industry leaders, and nonprofit innovators gathered at Cornell Tech for the inaugural Frontiers of AI Summit.