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Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the fly—a step toward building AI that continually improves itself.
One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing.
Researchers developed a machine learning model that can evaluate patients' PPD risk using readily accessible clinical and demographic factors.
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We then used machine learning algorithms trained on existing data to highlight novel genes or mutations shared across resistant strains that might contribute to resistance.
Recent years have seen the adoption of Machine Learning (ML) techniques to predict the performance of large-scale applications, mostly at a coarse level. In contrast, we propose to use ML techniques ...