Cambridge and NVIDIA had a full house at Harvard Med for the seminar entitled AI Futures at Harvard Medical School. GPU in EDU is a seminar series co-produced by NVIDIA and Cambridge Computer. We travel to universities and research institutions across the country to share ideas and insights related to AI and ML at the intersection of science and IT infrastructure. The content of each session is tailored to the specific interests of the institution hosting the event. Harvard Med chose to focus on deep learning for genomics, NVIDIA software frameworks, and GPU resource management.
We’d like to thank our friends at Harvard, Run:ai, and NVIDIA for making this event possible. Their support and collaboration were instrumental in making it a memorable and informative event. Special thanks for Run:ai for co-sponsoring the event and sharing insights into their amazing technology for pooling and scheduling GPU resources. We’d also like to thank Christos Alexiadis (Cambridge) and Eliot Eshelman (NVIDIA) for all their work behind the scenes.