TPUv7 offers a viable alternative to the GPU-centric AI stack has already arrived — one with real implications for the economics and architecture of frontier-scale training.

TPUs, on the other hand, are specialized in the sense that they only focus on certain processes. You can’t run a computer on a TPU: these chips are meant for fast tensor/matrix math. They don’t aim to ...

In our Geekbench CPU test, the Tensor G4 didn't perform well and it trailed behind last year's Tensor G3 in multi-core tasks. The 7-core ARM Mali-G715 GPU performance is nearly the same as last year, ...

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 ...

Tensor is a Silicon Valley based startup that plans to be the first company to sell a true robocar (Link goes live at 10am PDT) with “eyes off” self-driving ability and a steering wheel that folds ...

Hi, thanks for your great work on Transformer Engine! I am working on a project that requires high-performance batched matrix multiplication (i.e., 3D tensor multiplication) where all inputs are ...

Abstract: We investigate the performance of algorithms for sparse tensor-sparse tensor multiplication (SpGETT). This operation, also called sparse tensor contraction, is a higher order analogue of the ...