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Penn analysis found that models developed to detect depression using language in Facebook posts did not work when applied to Black people.
Researchers from Penn develop a framework for quantifying common sense, findings address a critical gap in how knowledge is understood.
Xander Uyttendaele, a 2023 graduate, is among 16 selected nationwide to receive the scholarship.
As AI gets more adept at synthesizing information and producing humanlike responses, many are concerned that malicious actors may use this technology in dangerous ways. Ph.D. candidate Alex Robey safeguards AI systems against malicious tampering.
Researchers from Penn have developed a framework for assessing generative AI’s efficacy at deciphering images.
Kevin B. Johnson, Jina Ko, and Sheila Shanmugan awarded NIH Common Fund’s High-Risk, High-Reward Research program.
Weitzman’s Masoud Akbarzadeh discusses a recent multidisciplinary study that draws inspiration from dragonfly wings to redesign a Boeing 777 to be lighter, stronger, and more sustainable.
Penn Integrates Knowledge Professor Konrad Kording will lead Penn’s NIH-funded cohort for making advancements in the field of machine learning in biomedical research by creating the Community for Rigor, which will provide open-access resources on conducting sound science.
A new study from Penn Medicine finds a steady increase in expressions of loneliness and depression as the pandemic continued.
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.
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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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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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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Benjamin Lee of the School of Engineering and Applied Science says that the electrical grid will have to figure out how to match supply and demand during brief windows where the energy source goes away.
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