The infrastructure supporting global computing is undergoing a massive shift. True computing power no longer belongs to isolated corporate data centers, but to open, global networks. Speaking at the ...

I've been writing about Android since 2011, with a focus on device reviews, Samsung and Google Pixel hardware, and the latest happenings in the ecosystem. In my entire writing career, I've reviewed ...

Abstract: The communication bottleneck severely constrains the scalability of distributed deep learning, and efficient communication scheduling accelerates distributed DNN training by overlapping ...

Steve was a Senior Writer at AP, where he covered over 40 smartphones a year. Steve has carried the latest and greatest around in his pocket for nearly 30 years, with everything from Motorola StarTACs ...

There is a huge gap between what AI can already do today and what most people are actually doing with it. Closing that gap will take years. Meanwhile, fortunes will be created, not just for giant tech ...

Google's TorchTPU aims to enhance TPU compatibility with PyTorch Google seeks to help AI developers reduce reliance on Nvidia's CUDA ecosystem TorchTPU initiative is part of Google's plan to attract ...

Tensor's Robocar has been custom built for Level 4 autonomy. Most people agree that full autonomy will be a big part of the future of driving. The question is when. Tesla may have been making all the ...

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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

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 ...