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 ...

Robotaxis are expanding into a growing number of cities, but an AI company called Tensor unveiled a self-driving vehicle on Wednesday designed specifically for personal ownership. Tensor says the ...

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 ...

There are central processing units (CPUs), graphics processing units (GPUs) and even data processing units (DPUs) – all of which are well-known and commonplace now. GPUs in particular have seen a ...

Activeloop, creator of a database platform that’s designed to cater specifically to artificial intelligence workloads, said today it has closed on an $11 million early-stage funding round, bringing ...

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 ...

The launch of the Tensor G5 at the Made by Google 2025 event marks a pivotal moment in smartphone technology, designed to power the latest Pixel 10 series with unmatched AI capabilities and ...

Google Tensor has always pitched itself on AI, and when it launched in 2021, it blew away the competition. But, now, the Snapdragon 8 Gen 3 is showing off truly incredible on-device AI capabilities, ...

Another Pixel phone, another Tensor system-on-a-chip from Google. That's basically where we're at this year: The company officially announced the Pixel 8 and Pixel 8 Pro at its Made by Google event on ...

A new RISC-V Tensor Unit, based on fully customizable 64-bit cores, claims to provide a huge performance boost for artificial intelligence (AI) applications compared to just running software on scalar ...

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.

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