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In advance of Perry World House’s Global Shifts Colloquium on extreme heat in urban areas, Penn Today spoke with chief heat officers about their role in influencing public awareness, preparedness, and policy.
Hosted by the Kleinman Center for Energy Policy and the Vagelos Institute for Energy Science and Technology, the third annual Energy Week, which runs March 20-24, offers events on decarbonization, careers in the energy sector, global energy security, and more.
A new edition of “Philadelphia Trees,” coauthored by former Morris Arboretum director Paul W. Meyer, Catriona Bull Briger, and Edward Sibley Barnard offers tips for identifying tree species and highlights some of the most notable trees in the region, including many on Penn’s campus.
New research from Penn’s School of Veterinary Medicine demonstrates that Yersinia pseudotuberculosis, a relative of the bacterial pathogen that causes plague, triggers the body’s immune system to form lesions in the intestines called granulomas.
Penn computer scientists prove that people can be trained to tell the difference between AI-generated and human-written text. Their new paper debuts the results of the largest-ever human study on AI detection.
Seven fourth-year students and one May graduate have each received a 2023 Thouron Award to pursue graduate studies in the United Kingdom.
As garden supervisor for the treasured green space formally known as the James G. Kaskey Memorial Park, Kuracina plans, plants, waters, and weeds, aiming to make it ‘more beautiful and special every year.’
AI models like ChatGPT have seen notable improvements, but some people are concerned about the societal impacts these new technologies may bring. Deep Jariwala and Benjamin C. Lee discuss energy and resource problems with AI computing.
Penn Engineering’s Shirin Saeedi Bidokhti and Saswati Sarkar have produced a suite of studies that apply techniques from network and information theory to pandemic control and prevention.
An international team of researchers led by Penn geneticists sequenced the genomes of 180 indigenous Africans. The results shed light on the origin of modern humans, African population history, and local adaptation.
Chris Callison-Burch of the School of Engineering and Applied Science discusses Penn’s new online master’s program in artificial intelligence.
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The School of Engineering and Applied Science has announced the first graduate program in artificial intelligence among Ivy League universities, led by Chris Callison-Burch.
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The School of Engineering and Applied Science has announced the first graduate program in artificial intelligence among Ivy League universities, led by Chris Callison-Burch.
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César de la Fuente of the School of Engineering and Applied Science and Perelman School of Medicine says that Neanderthal DNA provides insights into human evolution, population dynamics, and genetic adaptations, including correlations with traits such as immunity and susceptibility to diseases.
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A research team led by Michael Mann of the School of Arts & Sciences is predicting the upcoming Atlantic hurricane season will produce the most named storms on record, fueled by exceptionally warm ocean waters and an expected shift from El Niño to La Niña.
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Benjamin Lee of the School of Engineering and Applied Science says that hardware and infrastructure costs are growing at high rates for generative AI.
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Michael Mann of the School of Arts & Sciences explains how three low-pressure systems formed a train of storms that battered the United Arab Emirates.
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The “My Climate Story” project at the Environmental Humanities Department helps students and teachers learn about climate change’s impact in everyday backyards, with remarks from Bethany Wiggin. The idea is credited to María Villarreal, a College of Arts and Sciences second-year from Tampico, Mexico.
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Michael Mann of the School of Arts & Sciences says that many people blaming cloud seeding for Dubai storms are climate change deniers trying to divert attention from what’s really happening.
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Chris Callison-Burch of the School of Engineering and Applied Science says that auto-regressive generation can make it difficult for language learning models to perform fact-based or symbolic reasoning.
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