Amazon’s AWS cloud unit announced new chips for customers to build and run artificial intelligence applications on, as well as offering access to Nvidia’s latest chips.

Amazon Web Services is trying to stand out as a cloud provider with a variety of cost-effective options. It won’t just sell cheap Amazon-branded products, though. Just as in its online retail marketplace, Amazon’s cloud will feature top-of-the-line products. Specifically, that means highly sought after GPUs from top AI chipmaker Nvidia.

The dual-pronged approach might put AWS in a better position to go up against its top competitor. Earlier this month Microsoft took a similar dual-pronged approach by revealing its inaugural AI chip, the Maia 100, and also saying the Azure cloud will have Nvidia H200 GPUs.

Normally, the introduction of an AI chip from a cloud provider might present a challenge to Nvidia, but in this case, Amazon is simultaneously expanding its collaboration with Nvidia. At the same time, AWS customers will have another option to consider for AI computing if they aren’t able to secure the latest Nvidia GPUs.

Specifically, AWS announced its new Trainium2 artificial intelligence chip and the general-purpose Graviton4 processor during its Reinvent conference in Las Vegas on Tuesday. The company also said it will offer access to Nvidia’s latest H200 AI graphics processing units.

The new GPU is an upgrade from the H100, the chip OpenAI used to train its most advanced large language model, GPT-4. Big companiesstartups and government agencies are all vying for a limited supply of the chips.

The key improvement with the H200 is that it includes 141GB of next-generation “HBM3” memory that will help the chip perform “inference,” or using a large model after it’s trained to generate text, images or predictions. Nvidia has said the H200 will generate output nearly twice as fast as the H100. That’s based on a test using Meta’s Llama 2 LLM.

Demand for Nvidia GPUs has skyrocketed since startup OpenAI released its ChatGPT chatbot last year, wowing people with its abilities to summarize information and compose human-like text. It led to a shortage of Nvidia’s chips as companies raced to incorporate similar generative AI technologies into their products.

Amazon is the leader in cloud computing but has been renting out GPUs in its cloud for over a decade. In 2018 it followed cloud challengers Alibaba and Google in releasing an AI processor that it developed in-house, giving customers powerful computing at an affordable price.

The Graviton4 processors are based on Arm architecture and consume less energy than chips from Intel or AMD. Graviton4 promises 30% better performance than the existing Graviton3 chips, enabling what AWS said is better output for the price. Inflation has been higher than usual, inspiring central bankers to hike interest rates. Organizations that want to keep using AWS but lower their cloud bills to better deal with the economy might wish to consider moving to Graviton.

More than 50,000 AWS customers are already using Graviton chips. Startup Databricks and Amazon-backed Anthropic, an OpenAI competitor, plan to build models with the new Trainium2 chips, which will boast four times better performance than the original model, Amazon said.

AWS has launched more than 200 cloud products since 2006, when it released its EC2 and S3 services for computing and storing data. Not all of them have been hits. Some go without updates for a long time and a rare few are discontinued, freeing up Amazon to reallocate resources. However, the company continues to invest in the Graviton and Trainium programs, suggesting that Amazon senses demand.

AWS didn’t announce release dates for virtual-machine instances with Nvidia H200 chips, or instances relying on its Trainium2 silicon. Customers can start testing Graviton4 virtual-machine instances now before they become commercially available in the next few months.

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