September 2025

The Triangle AI Summit aimed to deepen engagement with AI and develop leadership to contend with its potential and risks

“We know that dialogue and collaboration are the way forward in charting our future with AI,” Provost Alec Gallimore said during opening remarks.

Hosted by Provost Alec Gallimore on May 30, the summit included a keynote by New York Times technology reporter Cade Metz and countless panels on AI’s impacts on society and its role in scientific innovation. Speakers engaged with AI’s dangers and potential, how AI is transforming the workforce and higher education, and why AI is not poised to replace humans just yet. 

Drawing an audience of approximately 450 in person and another 160 via livestream, the summit’s topics ranged from AI “hallucinations” to the use of AI technologies to detect strokes in brain scans. The event also included demos of how educators are using AI in the classroom and a panel of Code+ Duke students sharing their perspectives on AI. 

The summit included a student panel, a teaching showcase of more than 20 demos on how to use AI in the classroom, and two interactive workshops on using AI as task-oriented assistants.

A new Duke-developed AI system fuses vision, vibrations, touch and its own body states to help robots understand and move through difficult in-the-wild environments. Researchers from Duke University have developed a novel framework named WildFusion to enable robots to “sense” complex outdoor environments much like humans do.

“WildFusion opens a new chapter in robotic navigation and 3D mapping,” said Boyuan Chen, the Dickinson Family Assistant Professor of Mechanical Engineering and Materials Science, Electrical and Computer Engineering, and Computer Science at Duke University. “It helps robots to operate more confidently in unstructured, unpredictable environments like forests, disaster zones and off-road terrain.”

Reflecting Duke University’s leadership in AI development, implementation, and research, Provost Alec Gallimore launched a collaborative strategic AI initiative in May designed to bring together Duke experts across all disciplines who are advancing AI research, addressing the most pressing ethical challenges posed by AI, and shaping the future of AI in the classroom. A steering committee and four pillar advisory committees were formed to identify Duke’s priorities around AI and propose recommendations to guide how the pillars are developed and applied across the university. 

Following a kick-off reception on September 3, the steering and pillar advisory committees will meet throughout the semester and submit a report of recommendations in December.  

Through a pilot with OpenAI, Duke University now provides a prepaid license for ChatGPT to all undergraduate students, as well as faculty, staff and graduate and professional students from participating academic units. ChatGPT joins Duke's suite of AI platforms, which includes additional tools for everyday use like Microsoft Copilot and Zoom AI companion. In addition, Duke-managed tools, which are DukeGPT, MyGPT Builder, and AI Gateway for developers, allow users to explore and compare AI models, create custom AI environments, and build apps and tools, respectively. Whether you are involved in AI research and development, or want to learn how to start using AI to power your own work, Duke is here to help.

Want to learn more about the AI tools available to you at Duke? Our new webpage includes:

Duke University School of Medicine researchers have developed two pioneering frameworks designed to evaluate the performance, safety, and reliability of large-language models in health care.

Published in npj Digital Medicine and the Journal of the American Medical Informatics Association (JAMIA), these studies offer a new approach to ensuring that AI systems used in clinical settings meet the highest standards of quality and accountability.

Duke AI Health held the 12th Duke Machine Learning Summer School this June. The theme was Generative AI (MLSS-GenAI), with the course providing lectures on the fundamentals of generative artificial intelligence methods and applications. Curriculum was targeted to individuals interested in learning about generative AI, with a focus on recent deep learning methodologies. The course included lectures from a variety of Duke faculty experts, as well as case studies, and hands-on coding sessions to apply what was learned. Seminar teachers included an array of Duke faculty representing biostatistics, engineering, medicine, and biology, as well as former and current Duke AI Health Faculty Affiliates.

Reach out to us at dukeai@duke.edu with the details. 

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