Stevens Institute, Hoboken, reports the universal identity P²+K²=1, uniting polarization with entanglement across setups and ...

Light is usually described using quantum mechanics when phenomena like entanglement enter the picture. But a new paper shows ...

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

Picture a tune that plays with your mind. It does not go straight but skips and flips in ways you do not expect. That is math rock. It avoids common music paths, which makes it feel fresh and smart.

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 challenging tasks in numerical ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

Institut de Química Computacional, Universitat de Girona, Girona (Spain) and Ronin Institute, Montclair, NJ, USA. An in-depth description of an apparently forgotten matrix operation, the reversal ...

Graphics upscaling using AI is so important for gaming Sony decided to do its own hardware rather than use AMD technology. That's one of the most important take-homes from the signature deep dive Sony ...

Several fields of mathematics have developed in total isolation, using their own 'undecipherable' coded languages. Mathematicians now present 'big algebras,' a two-way mathematical 'dictionary' ...

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 ...