Hardware fragmentation remains a persistent bottleneck for deep learning engineers seeking consistent performance.

Streaming has undoubtedly changed how we watch movies. While nothing can replace the theatrical experience, the pros of streaming ultimately outweigh the cons. That being said, the prices are getting ...

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 ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

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 ...

Google DeepMind today pulled the curtain back on AlphaEvolve, an artificial-intelligence agent that can invent brand-new computer algorithms — then put them straight to work inside the company's vast ...

An optimized matrix multiplication library in C employing blocking, multithreading (POSIX threads), and SIMD (AVX) vectorization. It benchmarks algorithms against OpenBLAS and includes a theoretical ...

The Toyota Matrix was discontinued just over 10 years ago and it's already been pretty much forgotten. While it was dropped in the U.S. ahead of 2014 (and a year later for Canada), the Matrix had ...