Foundation models are AI systems trained on vast amounts of data — often trillions of individual data points — and they are capable of learning new ways of modeling information and performing a range ...
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New method improves the reliability of statistical estimations
MIT researchers have developed a method that generates more accurate uncertainty measures for certain types of estimation. This could help improve the reliability of data analyses in areas like ...
A new study published in AI Materials presents a comprehensive multi-scale computational framework capable of predicting the ...
Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...
Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...
Experts are increasingly turning to machine learning to predict antibiotic resistance in pathogens. With its help, resistance mechanisms can be identified based on a pathogen’s genetics. However, the ...
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