The company plans to start shipping the self-driving vehicle later this year. You'll also have the option to take over for a manual drive.

LAS VEGAS, Jan. 8, 2026 /PRNewswire/ -- At CES 2026, Tensor today announced the official open-source release of OpenTau ( ), a powerful AI training toolchain designed to accelerate the development of ...

A hunk of material bustles with electrons, one tickling another as they bop around. Quantifying how one particle jostles others in that scrum is so complicated that, beginning in the 1990s, physicists ...

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 ...

They managed to cut the size of the AI reasoning model by more than half—and claim it can now answer politically sensitive questions once off limits in Chinese AI systems. A group of quantum ...

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 ...

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 ...

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, ...

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 ...

(A) Illustration of a convolutional neural network (NN) whose variational parameters (T) are encoded in the automatically differentiable tensor network (ADTN) shown in (B). The ADTN contains many ...