Memory swizzling is the quiet tax that every hierarchical-memory accelerator pays. It is fundamental to how GPUs, TPUs, NPUs, and nearly all AI chips operate. It’s also a growing liability. Swizzling ...

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 ...

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 ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

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 ...

Google’s in-house Tensor chips have steadily improved over the years to become a reliable daily driver with solid battery efficiency. Still, performance has often been a sticking point. While previous ...

Google’s Tensor reboot of the Pixel lineup has never been about adding more power, but rather about creating an experience tailored to what Google wants your phone to be. With the Pixel 10, Tensor G5 ...

Abstract: Recently, fully-connected tensor network (FCTN) decomposition, which factorizes the target tensor into a series of interconnected factor tensors, has drawn growing focus on multi-dimensional ...

Google introduced its new Pixel 10 on Wednesday, and it features Google’s own new Tensor G5 chip, which the company says is 34 percent faster than its predecessor. That sounds great for Pixel ...

Abrar's interests include phones, streaming, autonomous vehicles, internet trends, entertainment, pop culture and digital accessibility. In addition to her current role, she's worked for CNET's video, ...