Google first announced that Sycamore had passed the RCS benchmark in 2019, when scientists used the chip to resolve a problem that would have taken a classical supercomputer 10,000 years to calculate.

Google's PaLM model - its largest publicly disclosed language model to date - was trained by splitting it across two of the 4,000-chip supercomputers over 50 days.

In a recent paper, Google revealed that their supercomputer is 1.7 times faster and 1.9 times more energy-efficient than a system based on Nvidia‘s A100 chip for a system of the same size.

According to Google researchers, the TPU v4 supercomputer, is "1.2x-1.7x faster and uses 1.3x-1.9x less powerful than the Nvidia A100." While Google creates, and conducts research on, AI systems ...

Google signs the largest corporate fusion power deal to date, aiming to supply AI-scale energy through its partnership with ...

Elon Musk’s artificial intelligence startup attained an official permit to power its Memphis supercomputer facility using ...

Experiments on Google's 67-qubit Sycamore processor showed operations entering a new "weak noise phase" in which calculations were complex enough to outperform supercomputers, based on benchmark ...

Alphabet Inc.’s Google has agreed to purchase 200 megawatts of power from Commonwealth Fusion System’s planned first ...

At the recent Google Cloud Next 2025 event, the tech giant claimed that its new Ironwood TPU v7p pod is 24 times faster than El Capitan, the exascale-class supercomputer at Lawrence Livermore ...

Google unveils Ironwood, its seventh-generation TPU chip delivering 42.5 exaflops of AI compute power — 24x more than the world's fastest supercomputer — ushering in the "age of inference." ...

Google first announced that Sycamore had passed the RCS benchmark in 2019, when scientists used the chip to resolve a problem that would have taken a classical supercomputer 10,000 years to calculate.