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.

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 ...

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.

Google has designed its own custom chip called the Tensor Processing Unit, or TPU. It uses those chips for more than 90% of the company's work on artificial intelligence training.

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." ...

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 ...

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.