AI News + Events
The latest AI breakthroughs, news, and events across Cornell.
Event Spotlight
AI4AI Fall Retreat
Tues. Oct. 27, 2026 @ Cornell Tech, NYC
The AI4AI Fall Retreat is a one-day convening of researchers and industry partners advancing the Assured Integrity for AI-Based Software (AI4AI) initiative. Bringing together collaborators from Cornell and across industry, the retreat focuses on sharing research progress, shaping emerging priorities, and accelerating real-world impact in AI security. The event is designed to foster deeper collaboration between academia and practice, with an emphasis on advancing trustworthy, secure AI systems and translating research into tools and approaches that benefit the broader community.
Researchers gather at Cornell Tech to explore AI for molecular science
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.
Weak AI regulation may backfire, making products less safe
A new modeling study finds no regulation of AI products and services may be safer than weak regulation.
At Cornell, 4-H’ers plant seeds for future careers
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.
Alums launch company to streamline cash flow processes
The newest podcast from Entrepreneurship at Cornell features the founders of Tabs.
AI research team could streamline clinical trial design
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.
Inside baseball: AI-enabled enforcement tech takes time, testing
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.
Speeding up a manual process helps Cornell recover $100,000
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.
Can AI plan for heat emergencies better than simple rules? It depends
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.
Matt Marx named vice provost for entrepreneurship, innovation and external engagement
Marx will establish and serve as inaugural director of the Cornell Center for Entrepreneurship and Innovation, to boost university efforts to commercialize breakthrough scientific discoveries.
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