There could be a new era of codesign dawning for machine learning, one that moves away from the training and inference separations and toward far less dense networks with highly sparse weights and ...

Sparsity is a measured way of optimizing machine learning models by deliberately specifying which nodes are composed of zero values. Sparse models, as opposed to dense models, contain mostly zero ...

Suppose you have a thousand-page book, but each page has only a single line of text. You’re supposed to extract the information contained in the book using a scanner, only this particular scanner ...

A new technical paper titled “Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention” was published by DeepSeek, Peking University and University of Washington.