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Maia 200 AI chip promises threefold FP4 power, edging out TPU and Trainium in inference
technology2 months ago

Maia 200 AI chip promises threefold FP4 power, edging out TPU and Trainium in inference

Microsoft unveiled Maia 200, an AI inference accelerator for Azure, claiming it delivers over 10 petaflops at FP4 and 5 PFLOPS at FP8, with 3x FP4 performance versus Amazon’s Trainium Gen3 and FP8 performance above Google’s TPU Gen7. Built on TSMC’s 3-nanometer process with about 100 billion transistors, Maia 200 is designed for data-center inference to speed Copilot and Azure OpenAI workloads, featuring a memory system to keep model weights local and is currently deployed in a US data center with broader Azure availability planned in the future.

via Live Science|
#ai-chip#fp4#maia-200
"Google Introduces Arm-Based Data Center Processor and AI Chip"
technology2 years ago

"Google Introduces Arm-Based Data Center Processor and AI Chip"

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.

via Reuters|
#ai#arm-based-processor#data-center
Google's Gemini Pro: Revolutionizing AI in Business with Vertex AI Tools
technology2 years ago

Google's Gemini Pro: Revolutionizing AI in Business with Vertex AI Tools

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.

via ZDNet|
#ai-studio#gemini-pro#google
Google's AI supercomputer outperforms Nvidia A100 in speed and energy efficiency.
technology3 years ago

Google's AI supercomputer outperforms Nvidia A100 in speed and energy efficiency.

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.

via Reuters|
#ai#google#nvidia
Google's AI supercomputer outperforms Nvidia's A100 chip.
technology3 years ago

Google's AI supercomputer outperforms Nvidia's A100 chip.

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.

via Yahoo Canada Finance|
#ai#google#nvidia
technology3 years ago

Google's AI supercomputer outperforms Nvidia's A100 chip.

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.

via Yahoo Finance|
#ai#google#nvidia