"Or as AWS puts it: customers supply the power and the data center, and AWS plunks in the AI system, manages it, and can tie it into other AWS cloud services. The idea is to cater to companies and governments concerned with data sovereignty, or absolute control over their data so it can't wind up in a competitor's or foreign adversary's hands. An on-prem AI Factory means not sending their data to a model maker, and not even sharing the hardware."
"In this case, the AWS Factory will use a combination of AWS and Nvidia technology. Companies that deploy these systems can opt for Nvidia's latest Blackwell GPUs or Amazon's new Trainium3 chip. It uses AWS' homegrown networking, storage, databases and security and can tap into Amazon Bedrock - the AI model selection and management service, and AWS SageMaker AI, the model building and training tool."
"In October, Microsoft showed off its first of many-to-come AI Factories rolling out into its global data centers to run OpenAI workloads. Microsoft didn't announce at the time that these extreme machines would be available for private clouds. Instead, Microsoft highlighted how it was leaning on a host of Nvidia AI Factory data center tech to build and connect its new "AI Superfactories," aka new state-of-the-art data centers being built in Wisconsin and Georgia."
AWS introduced AI Factories to place AWS-managed AI systems inside customer data centers while customers provide power and facilities. The offering aims to ensure data sovereignty by preventing data or hardware from leaving customer premises. The service is built in collaboration with Nvidia and offers hardware options including Nvidia Blackwell GPUs or Amazon Trainium3 chips. The solution integrates AWS networking, storage, databases, Bedrock model management, and SageMaker training tools. Similar Nvidia-based on-prem deployments are appearing across other cloud providers, and Microsoft has showcased comparable AI Superfactories and plans local data centers to address sovereignty requirements.
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