Abstract: The increasing complexity and scale of Deep Neural Networks (DNNs) necessitate specialized tensor accelerators, such as Tensor Processing Units (TPUs), to meet various computational and ...

Google’s system leverages optical circuit switching (OCS) to create direct, low-latency optical paths between TPU chips, minimizing signal conversion losses. They avoid repeated ...

Ars Technica has been separating the signal from the noise for over 25 years. With our unique combination of technical savvy and wide-ranging interest in the technological arts and sciences, Ars is ...

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 ...

Researchers have demonstrated a new optical computing method that performs complex tensor operations in a single pass of light. The advance could reshape how modern AI systems process data and ease ...

Taking a look back at this week’s news and headlines across the Android world, including Galaxy S26 delay, Samsung’s Galaxy XR Headset, measuring the Pixel’s Tensor G5, Nubia’s 35mm camera system ...

Parth is a technology analyst and writer specializing in the comprehensive review and feature exploration of the Android ecosystem. His work is distinguished by its meticulous focus on flagship ...

Internally, aggregate will validate invariants, synchronize CQs of individual devices, and return Tensor object allocated on the parent MeshDevice. It will also synchronize the state of the parent ...

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 ...

D.A. Davidson values Google’s TPU and DeepMind unit at $900B if spun off. Rising demand for cost-efficient TPUs boosts Alphabet’s AI market position. Analysts lift Alphabet target to $190 but keep a ...