NVIDIA’s rise from graphics card specialist to the most closely watched company in artificial intelligence rests on a ...

FICO Xpress 9.8 features a GPU-accelerated implementation of the hybrid gradient algorithm, yielding up to 50x speedups for very large optimization problems FICO Xpress Optimization has the widest ...

What just happened? Since its introduction in 2006, CUDA has been a proprietary technology running exclusively on Nvidia's own GPU hardware. Now, the GeForce maker appears ready to open CUDA to at ...

Apple’s MLX machine learning framework, originally designed for Apple Silicon, is getting a CUDA backend, which is a pretty big deal. Here’s why. The work is being led by developer @zcbenz on GitHub ...

Why it matters: Nvidia introduced CUDA in 2006 as a proprietary API and software layer that eventually became the key to unlocking the immense parallel computing power of GPUs. CUDA plays a major role ...

CUDA and Tensor Cores are some of the most prominent specs on an NVIDIA GPU. These cores are the fundamental computational blocks that allow a GPU to perform a bunch of tasks such as video rendering, ...

Today, Nvidia’s revenues are dominated by hardware sales. But when the AI bubble inevitably pops, the GPU giant will become the single most important software company in the world. Since ChatGPT ...

In this photo illustration the Nvidia logo is shown on a mobile phone against the illustration of a stock market graph illustration displayed on a computer screen Nvidia reported third-quarter revenue ...

Nvidia’s data center chips have become the default engine for modern artificial intelligence, but they are not just faster versions of gaming graphics cards. The company’s AI accelerators strip away ...