All articles tagged with #tpu
Originally Published 2 months ago — by Seeking Alpha
Google is set to launch its seventh-generation Tensor Processing Unit, named Ironwood, in the coming weeks, aiming to enhance its AI hardware capabilities and challenge Nvidia in the market.
Originally Published 1 year ago — by Reuters
Google unveiled a new version of its data center artificial intelligence chips, called TPU v5p, and announced an Arm-based central processor named Axion, which offers superior performance to x86 chips. The company plans to offer Axion via Google Cloud and aims to power services such as YouTube Ads in Google Cloud "soon." The TPU v5p chip is built to run in pods of 8,960 chips and can achieve twice the raw performance as the prior generation of TPUs. This move positions Google to compete with other cloud operators and provides developers with an alternative to Nvidia's AI chips.
Originally Published 2 years ago — by ZDNet
Google has made its top-of-the-line artificial intelligence program, Gemini Pro, available as a preview version in its AI Studio programming tool and Vertex AI for enterprise users. Gemini is part of Google's AI hyper-computing infrastructure and utilizes the Tensor Processing Unit (TPU) for enhanced performance. The AI Studio allows individuals and small teams to build applications using natural-language prompting, while Vertex AI is designed for enterprise use with access to corporate data sources. Google Cloud also announced the availability of TPU v5p, which offers four times the performance of the previous version. Gemini Pro is one of three versions, with Ultra in private preview and Nano set for release on mobile devices. Additionally, Google introduced Imagen 2, an enhanced text-to-image neural network, available in the Vertex AI feature called Model Garden.
Originally Published 2 years ago — by Reuters
Google has revealed that its custom-designed Tensor Processing Unit (TPU) supercomputer is faster and more power-efficient than comparable systems from Nvidia. The TPU is now in its fourth generation and is used for over 90% of Google's work on artificial intelligence training. Google has strung more than 4,000 of the chips together into a supercomputer using its own custom-developed optical switches to help connect individual machines. The company's largest publicly disclosed language model to date was trained by splitting it across two of the 4,000-chip supercomputers over 50 days. Google hinted that it might be working on a new TPU that would compete with the Nvidia H100 but provided no details.
Originally Published 2 years ago — by Yahoo Canada Finance
Google has revealed that its custom-designed Tensor Processing Unit (TPU) is faster and more power-efficient than Nvidia's A100 chip. The TPU is used for over 90% of Google's artificial intelligence training, and the company has strung over 4,000 of the chips together into a supercomputer using its own custom-developed optical switches. 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. Google hinted that it might be working on a new TPU that would compete with Nvidia's H100 chip but provided no details.
Originally Published 2 years ago — by Yahoo Finance
Google has revealed that its custom-designed Tensor Processing Unit (TPU) supercomputer is faster and more power-efficient than comparable systems from Nvidia. The TPU is now in its fourth generation and is used for over 90% of Google's work on artificial intelligence training. Google has strung more than 4,000 of the chips together into a supercomputer using its own custom-developed optical switches to help connect individual machines. The company said its chips are up to 1.7 times faster and 1.9 times more power-efficient than a system based on Nvidia's A100 chip that was on the market at the same time as the fourth-generation TPU.