A new technical paper titled “Hardware Acceleration for Neural Networks: A Comprehensive Survey” was published by researchers ...

The number of AI inference chip startups in the world is gross – literally gross, as in a dozen dozens. But there is only one ...

This video reveals how tensors quietly power the mathematics behind the physical world, from motion and forces to space, time, and modern physics. Learn what tensors really are, why they appear ...

Systolic arrays are fundamental building blocks for efficient matrix multiplication and ML accelerators (e.g., Google TPU, tensor cores). A reusable, well-tested systolic array library would benefit ...

The AI model makers of the world have been waiting for more than a year to get their hands on the Trainium3 XPUs, which have been designed explicitly for both training and inference and which present ...

Tensor was founded in Silicon Valley as AutoX back in 2016 and focused on building autonomous commercial vehicles and robotaxis. The company began testing autonomous vehicles in California and China ...

When the FORTRAN programming language debuted in 1957, it transformed how scientists and engineers programmed computers. Complex calculations could suddenly be expressed in concise, math-like notation ...

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 ...

Tensors are the fundamental building blocks in deep learning and neural networks. But what exactly are tensors, and why are they so important? In this video, we break down the concept of tensors in ...

Blood pressure is the amount of pressure that your blood exerts on the blood vessels in your body. As your heart beats, it contracts and relaxes, pushing blood out of the heart to the arteries, which ...

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics. The ...