AI Bias Analysis
4 models · Takes ~15 seconds
Listen to this audio excerpt from Dan Florez, test director for NASA’s Exploration Ground Systems Program: At 1:47 a.m. EST November 16, 2022, as the Artemis I engines ignited, NASA astronaut Reid Wiseman and Dan Florez, NASA test director for the agency’s Exploration Ground Systems, watched from Kennedy’s Launch Control Center roof as the midnight […]
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NASA
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Researchers at the Department of Energy's Oak Ridge National Laboratory developed a method to convert a commonly discarded hydrocarbon polymer into gasoline- and diesel-like fuels. The team has applied for a patent for the discovery, which treats polyethylene—the stuff of white cutting boards and shopping bags—with aluminum chloride-containing molten salts that serve as both solvent and catalyst. The results are published in the Journal of the American Chemical Society.
As large floods occur more frequently worldwide, many wonder what led to such devastating events. Greenhouse gas emissions from human activities, improper land management and forest removal increase flood frequencies and severity.
Daily travel plans and early warnings for extreme weather all rely on traditional numerical weather prediction. However, both traditional numerical weather prediction and AI forecasting large models have long suffered from systematic biases, which compromise forecast accuracy.
Professor Gyu Rie Lee of the Department of Biological Sciences successfully designed artificial proteins that selectively recognize specific compounds using AI through joint research with Professor David Baker. The research, published in the journal Nature Communications, is characterized by using AI to design proteins that recognize specific compounds from scratch (de novo) and implementing them as functional biosensors.
