Chinese AI chip start-up Zhonghao Xinying has emerged as a home-grown alternative to Nvidia with a new tensor processing unit (TPU), just as Google shakes up Nvidia's lock on the market by selling its ...

A custom-built chip for machine learning from Google. Introduced in 2016 and found only in Google datacenters, the Tensor Processing Unit (TPU) is optimized for matrix multiplications, which are ...

Amid ongoing US export restrictions, Chinese company Zhonghao Xinying plans to launch its second-generation self-developed ...

The Google Tensor G5 has been announced, and the company claims that it brings the biggest leap in performance yet, as far as Tensor chips are concerned. This is the first TSMC-made Tensor chip with a ...

Scientists in China have developed a tensor processing unit (TPU) that uses carbon-based transistors instead of silicon – and they say it's extremely energy efficient. When you purchase through links ...

Will Google’s TPU (Tensor Processing Unit) emerge as a rival to NVIDIA’s GPU (Graphics Processing Unit)? Last month, Google announced its new AI model ‘Gemini 3,’ stating, “We used our self-developed ...

A processing unit in an NVIDIA GPU that accelerates AI neural network processing and high-performance computing (HPC). There are typically from 300 to 600 Tensor cores in a GPU, and they compute ...

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 ...

Dan Fleisch briefly explains some vector and tensor concepts from A Student’s Guide to Vectors and Tensors. In the field of machine learning, tensors are used as representations for many applications, ...