Abstract: Accelerating matrix multiplication is crucial to achieve high performance in many application domains, including neural networks, graph analytics, and scientific computing. These ...

Abstract: The extraction and detection of weak faults of rolling bearings on rotating machinery are essential and crucial. However, traditional methods of sparse matrix optimization have shortcomings ...

In industrial recommendation systems, the shift toward Generative Retrieval (GR) is replacing traditional embedding-based nearest neighbor search with Large Language Models (LLMs). These models ...

In 1999, The Matrix was released to the world. At the time, it felt fantastical, almost absurd. The idea that machines could become so intelligent that they would no longer need humans, not to think, ...