Training models with billions or trillions of parameters demands advanced parallel computing. Researchers must decide how to combine parallelism strategies,...

Training models with billions or trillions of parameters demands advanced parallel computing. Researchers must decide how to combine parallelism strategies, select the most efficient accelerated libraries, and integrate low-precision formats such as FP8 and FP4—all without sacrificing speed or memory. There are accelerated frameworks that help, but adapting to these specific methodologies…

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​​For decades, one of biology’s deepest mysteries was how a string of amino acids folds itself into the intricate architecture of life. Researchers built...

​​For decades, one of biology’s deepest mysteries was how a string of amino acids folds itself into the intricate architecture of life. Researchers built painstaking simulations and statistical models, inching toward an answer but never crossing the threshold of prediction at scale. Then, deep learning changed everything. By learning the language of evolution directly from sequence data…

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