Through
4/26
Using a Penn-designed neural network called PocketMiner, a Penn Medicine research team has identified hidden protein pockets that can provide new opportunities for cancer drugs to bind to.
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.
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.
The 4th annual Women in Data Science @ Penn conference featured an array of impressive industry, academic, and student speakers, each of whom possesses unique insights into the study and application of data science.
Artist-in-residence and visiting scholar Rebecca Kamen has blended AI and art to produce animated illustrations representing how a dyslexic brain interprets information.
A team of researchers from the School of Engineering and Applied Science has introduced a computing architecture ideal for AI using an approach known as compute-in-memory.
Through the PURM internship program, Julia Youngman and Eric Tao had the opportunity to work in neuroethologist Marc Schmidt’s lab studying the neural basis of courtship behaviors in songbirds.
The Class of 2022 law student works to identify biases and ‘stereotype threat’ in AI and help provide context for the conversation around mitigating those biases.
Historian of science Elly Truitt’s multidisciplinary investigations of the Middle Ages challenge assumptions about the period as a dark time in innovation and prompt a rethink of notions of ‘modern’ science.
Drawing on field research, the assistant professor of sociology ,examines the specific real-world conditions under which software systems replace, complement, or create human labor.
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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David Hoffman of Penn Carey Law says that “generative interpretation” can replace the messy and expensive way lawyers currently hash out the meaning of words in legal agreements, using dictionaries and Latin canons.
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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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Sonny Tambe of the Wharton School says that AI is a useful tool for most people, not an existential threat.
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Mary Ritchie has been named the vice dean of artificial intelligence and computing at the Perelman School of Medicine. Mitchell Schnall has been named the first senior vice president for data and technology solutions at the University of Pennsylvania Health System.
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Ethan Mollick of the Wharton School is teaching his students to use and understand the capabilities of generative AI.
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