American Physical Society recognizes ORNL’s historic Graphite Reactor
Grant and Award Announcement
Updates every hour. Last Updated: 30-Apr-2025 10:08 ET (30-Apr-2025 14:08 GMT/UTC)
Renowned astronomer, Dr. Jill Tarter, SETI Institute co-founder and pioneering SETI researcher, will be honored with the inaugural Tarter Award for Innovation in the Search for Life Beyond Earth at the SETI Institute’s 40th Anniversary celebration on November 20, 2024, in Menlo Park, CA. This new award recognizes individuals whose projects or ideas significantly advance humanity’s search for extraterrestrial life and intelligence. The Tarter Award honors contributions across science, technology, education, art, philosophy, law and ethics that support SETI’s mission to search for life and intelligence beyond Earth.
“Anyone who has had the privilege of knowing Jill, knows one thing about her—she never, never gives up the fight for what she believes in,” said Jim Bildner who serves on the Tarter Award Selection Committee. “And the quest to search for life beyond our planet exists in no small part due to her tireless efforts over decades. And yes, as the inspiration to Carl Sagan for his character Ellie Arroway played by Jody Foster in Contact, she has inspired thousands of women to pursue their dreams in science and astronomy. In a world full of challenges, Jill shows us the power of one human life to make a difference in the lives of others."Covered recently in the prestigious journal Nature Medicine, BiomedGPT is a new a new type of artificial intelligence (AI) designed to support a wide range of medical and scientific tasks. This new study, conducted in collaboration with multiple institutions, is described in the article as "the first open-source and lightweight vision–language foundation model, designed as a generalist capable of performing various biomedical tasks."
"This work combines two types of AI into a decision support tool for medical providers," explains Lichao Sun, an assistant professor of computer science and engineering at Lehigh University and a lead author of the study. "One side of the system is trained to understand biomedical images, and one is trained to understand and assess biomedical text. The combination of these allows the model to tackle a wide range of biomedical challenges, using insight gleaned from databases of biomedical imagery and from the analysis and synthesis of scientific and medical research reports."
Three Texas A&M nuclear engineering Ph.D. students and one recent Ph.D. graduate won Rapid Turnaround Experiment funding to research new nuclear reactor materials.