IBM is setting its sights on a major upgrade in AI hardware, with the company in talks with AWS to access Nvidia’s highly sought-after AI chips.

The deal, worth an estimated $475 million over five years, would grant IBM access to AWS’s Elastic Compute Cloud (EC2) servers, which are powered by Nvidia GPUs. As part of the arrangement, IBM would also use AWS’s SageMaker platform to train its AI models.

Why Nvidia?

So, why all the fuss over Nvidia GPUs? It comes down to IBM’s growing AI ambitions, particularly its Watson platform. AI projects are becoming more complex and resource-intensive, and Nvidia GPUs are the industry favourite for handling heavy workloads. They’re fast, reliable, and purpose-built for training and deploying massive AI models.

Watson AI supports industries like healthcare and finance, where precision is critical. To stay competitive and meet growing demands, IBM needs top-tier technology. But it’s not just IBM—tech giants like Google and Meta are also vying for Nvidia GPUs to power their AI projects. Since IBM doesn’t produce its own chips, collaborating with AWS for Nvidia’s hardware isn’t just a strategic choice—it’s a necessity.

This deal could strengthen AWS’s position in the AI cloud market. AWS already offers a robust ecosystem for AI development, with tools like SageMaker making it easier for companies to train and deploy models. By working with AWS, IBM can scale its AI initiatives without investing in expensive hardware infrastructure.

AWS has been promoting its custom chips, Trainium and Inferentia, as less expensive and more energy-efficient alternatives to Nvidia GPUs. However, IBM’s decision to continue with Nvidia highlights Nvidia’s proven trust and performance. For the time being, Nvidia remains the top choice for companies that choose performance over pricing.

AWS’s AI business is growing rapidly. CEO Andy Jassy recently said it’s expanding at “triple-digit percentages” and could soon generate multibillion-dollar revenues. A partnership with IBM could push those numbers even higher while cementing AWS’s reputation as a leader in AI infrastructure.

For Nvidia, this is yet another confirmation of their market domination. Despite competition from AWS, Google, and Meta, its GPUs remain the first choice for advanced AI workloads.

However, rising demand has resulted in supply shortages, raising prices and creating fierce competition. For IBM and AWS, securing Nvidia GPUs is not just a strategic move—it’s essential for staying competitive in the AI race.

IBM and AWS have also deepened their collaboration with an expansion of IBM’s software offerings on AWS Marketplace. Previously available in just five countries, these tools are now accessible in 92. Businesses worldwide can now access IBM’s AI and data solutions, such as Watsonx.data and Watsonx.ai, as well as flagship offerings like Db2 Cloud Pak for Data.

This expansion highlights a growing trend of tech giants collaborating to meet the surging demand for cloud-native solutions. Analysts view it as a pivotal moment, signalling greater collaboration across the industry.

The big picture

Whether it’s Nvidia GPUs or expanded software access, IBM and AWS are forming a win-win partnership. IBM gets the tools it needs to scale its AI ambitions, AWS strengthens its rapidly growing AI business, and Nvidia cements its position as the backbone of AI hardware.

This collaboration reflects where the tech world is headed: collaborations that drive innovation. As AI reshapes industries, organisations that combine expertise and resources will be the ones to watch.

(Photo by Unsplash)

See also: Alibaba Cloud and NVIDIA merge AI prowess for next-gen automotive tech

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Tags: AI, AWS, cloud, IBM, NVIDIA