Connecting Research and Experts with Journalists

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The MiikeMineStamps dataset of stamps provides a unique window into the workings of a large Japanese corporation, opening unprecedented possibilities for researchers in the humanities and social sciences. But some of the stamps in this archive only appear in a small number of instances. This makes for a “long tail” distribution that poses particular challenges for AI learning, including fields in which AI has experienced serious failures. A collaboration between scientists at the University of Pittsburgh (Pitt), PSC, DeepMap Inc. of California and Carnegie Mellon University (CMU) took up this challenge, using PSC’s Bridges and Bridges-2 systems to build a new machine learning (ML) based tool for analyzing “long tail” distributions.

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Despite the lifesaving success of the COVID-19 vaccines, very rare side effects have emerged. Vaccines engineered from the otherwise-mild adenovirus, for example, have been linked to blood clots. Scientists from Arizona State University, the Mayo Clinic, AstraZeneca and elsewhere have performed simulations on PSC’s Bridges-2 system that suggest simple electrical charge may make a protein involved in blood clot formation stick to particles of the AstraZeneca vaccine. The discovery will be the foundation of an effort to explain how the side effect happens and how the vaccine can be re-engineered to prevent it.

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A team at Ohio University used the Pittsburgh Supercomputing Center’s Bridges-2 system to carry out a series of simulations showing how coal might eventually be converted to valuable — and carbon-neutral — materials like graphite and carbon nanotubes.

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We’ve learned a lot about the Universe from telescopes that are sensitive to anything from high-energy gamma waves to visible light to low-energy radio waves. But detecting such electromagnetic waves has limitations.

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We might think that, if you want to feed more people in areas with food insecurity, you can just grow more food. But it isn’t that simple.

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In a paper in the prestigious journal Science to appear on Feb. 29, 2024, a multi-institutional team led by scientists at Carnegie Mellon University and University of California at Berkeley found parts of the genome, both within genes and outside of them, that evolved and are associated with vocal learning across mammals. These elements have been linked to autism in humans.

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A Carnegie Mellon University-led team has used the Pittsburgh Supercomputing Center’s Bridges-2 system and input from different cultures to develop an effective fine-tuning approach for retraining a popular image generator so that it can generate equitable images for underrepresented cultures.