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HomeAI News & UpdatesAWS Has Introduced Trainium2, A Chip for Training AI Models.

AWS Has Introduced Trainium2, A Chip for Training AI Models.

In addition to announcing intentions to provide access to Nvidia‘s newest chips, Amazon Web Services (AWS) has also unveiled new chips that users can use to develop and execute AI applications. Amazon Web Services aims to differentiate itself as a cloud provider by offering a range of affordable solutions. However, it will provide more than only low-priced Amazon-branded items. Like in its online retail marketplace, you may expect top-tier products from other vendors on Amazon’s cloud. This includes the highly coveted GPUs from Nvidia, a leading AI chipmaker.

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As a result of startup OpenAI’s ChatGPT chatbot’s impressive summary and writing skills, demand for Nvidia GPUs has surged since its introduction last year. As other companies hurried to include comparable generative AI capabilities in their products, it caused a scarcity of Nvidia’s chips. Amazon hopes to gain ground on Microsoft, its main cloud computing rival, by combining its chip development with providing consumers access to Nvidia’s newest chips. Microsoft recently revealed the Maia 100, its first artificial intelligence processor, and said its cloud service Azure will contain Nvidia H200 GPUs, following a similar strategy. Customers and Nvidia will have access to a dedicated computer cluster hosted by AWS.

These announcements were made on Tuesday at the Reinvent conference in Las Vegas. In particular, AWS has announced that its customers would have access to the newest AI GPUs from Nvidia, the H200 series. It announced the general-purpose Graviton4 CPU and the new Trainium2 AI chip.

OpenAI could train its most sophisticated big language model, GPT-4, using the new Nvidia GPU instead of the older H100. Because of the intense competition for chips among large corporations, new businesses, and even government organizations, there is a considerable demand to rent them from cloud providers such as Amazon. Compared to the H100, Nvidia claims the H200 will provide output almost twice as quickly.

Artificial intelligence chatbots like OpenAI’s ChatGPT and similar products are trained on Amazon’s Trainium2 chips. According to Amazon, the new Trainium2 chips will have four times the performance of the old model. Startup Databricks and OpenAI rival Anthropic, which Amazon supports, intend to construct models using these chips.

Graviton4 CPUs use less power than Intel or AMD chips since they are based on the Arm architecture. According to AWS, Graviton4 will allow for better production for the price and boast 30% higher performance than the current Graviton3 processors. The very high inflation rate has prompted interest rate hikes by central banks. Graviton could be a good option for organizations looking to reduce their cloud expenditures while still using AWS, especially in light of the current economic climate. According to Amazon, Graviton chips are already in use by over 50,000 AWS customers.

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Lastly, AWS said that it will run over 16,000 Nvidia GH200 Grace Hopper Superchips, which include both Nvidia graphics processing units (GPUs) and Nvidia’s Arm-based general-purpose CPUs, as part of its growing partnership with Nvidia. This infrastructure will be accessible to both AWS customers and Nvidia’s internal R&D team.

Since the launching of its computing and data storage services, EC2 and S3, in 2006, AWS has introduced over 200 cloud products. Some of them have yet to gain traction. This allows Amazon to shift resources as some go without updates for a while, and a few are discontinued. Nonetheless, Amazon keeps pouring money into Graviton and Trainium, which could mean the corporation is picking up on demand.

AWS has yet to announce Virtual machine instances utilizing Nvidia H200 chips or its Trainium2 silicon. Graviton4 virtual machine instances will be offered for testing to customers in the coming months before they are made widely available.

Editorial Staff
Editorial Staff
Editorial Staff at AI Surge is a dedicated team of experts led by Paul Robins, boasting a combined experience of over 7 years in Computer Science, AI, emerging technologies, and online publishing. Our commitment is to bring you authoritative insights into the forefront of artificial intelligence.


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