Inverting a matrix is one of the most common tasks in data science and machine learning. In this article I explain why inverting a matrix is very difficult and present code that you can use as-is, or ...
Researchers from Fudan University designed a fiber integrated circuit (FIC) with a multilayered spiral architecture. The ...
Computer scientists are a demanding bunch. For them, it’s not enough to get the right answer to a problem — the goal, almost always, is to get the answer as efficiently as possible. Take the act of ...
Computer scientists have discovered a new way to multiply large matrices faster than ever before by eliminating a previously unknown inefficiency, reports Quanta Magazine. This could eventually ...
Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most difficult tasks in numerical ...
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Tiny silicon structures compute with heat, achieving 99% accurate matrix multiplication
MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat ...
MIT engineers use heat-conducting silicon microstructures to perform matrix multiplication with >99% accuracy hinting at ...
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