Opinion: AMD is poised for huge AI growth in 2024 and the market is paying attention

Starting off the company’s “Accelerate AI” event held in San Jose, Calif. on Wednesday, CEO Lisa Su tried to squelch some of that debate. One of the first slides she showed described how the projected TAM (total addressable market, or the market size to which AMD could potentially target with its chips) for data center AI accelerators through 2027 has increased to a projected $400 billion from $150 billion in just the last year. That is a growth rate of more than 70% for the next four years and justified Su’s parting words to her audience: “AI is absolutely the No. 1 priority at AMD.”

Witnessing the change in the company’s direction, its acceleration in its AI software development and engagement with partners, it’s easy to believe Su is telling the truth. AMD has projected that the MI300 family of products will bring at least a $2 billion revenue uplift, a bold statement for a company that typically is timid about projecting that much monetary confidence. 

But its AI-focused event detailed why AMD is confident in its products and its position versus competitors. Two new data center AI processors were announced, the Instinct MI300X and the MI300A. At a high level the MI300X is the competitor to traditional data center GPUs like the Nvidia H100, while the MI300A is a combination of CPU and GPU cores in a single package, creating a hybrid product similar to Grace Hopper from Nvidia and the delayed Falcon Shores project from Intel. 

Focus was on the MI300X product, as it is shipping and available now from several partners. AMD went into a lot of detail on its performance claims for the MI300X, all of which need some external third-party validation of course, including matching performance with the Nvidia H100 GPU in AI training workloads and 40-60% faster performance in AI inference workloads. The MI300X offers 192GB of memory per GPU, while the H100 is limited to 80GB and this is likely a big reason for the performance of AMD’s new chip.

Nvidia did announce the H200 just last month with up to 141GB of memory and better overall performance, but it isn’t available for testing yet so AMD couldn’t run any comparisons. 

Profitable AI ecosystem

The software ecosystem has been a big focus for AMD over the last year, ever since Su stepped on stage at CES in January 2023 to hold up the MI300 chip for the first time, promising big things for its AI strategy.

Nvidia’s lead with its CUDA development platform is still a significant hurdle, but AMD has made a lot of inroads, and the evolution of the AI ecosystem to more standardized models and frameworks is also helping. The release of a new version of its CUDA competitor, ROCm 6, includes many model optimizations and development library improvements. OpenAI has signed up to support the MI300 in its standard release going forward and AMD had representatives from AI companies including databricks and Lamini on stage backing up the software progress from AMD, with one even claiming it had “moved beyond CUDA.”

AMD also trotted out on stage a bevy of Big Tech names including Microsoft
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Microsoft announced immediate availability of MI300X based instances in its Azure cloud infrastructure and Dell announced it was ready to take orders.

These are important milestones for AMD. Because it doesn’t have the market dominance that Nvidia does, AMD requires the support of partners to help sell its product. Luckily for AMD, the shortage of Nvidia GPUs in the market has created a void and plenty of hungry partners that need to fill orders. 

For Nvidia this announcement isn’t a surprise, and the company has been preparing for its arrival since AMD first announced the MI300 back in 2022. The H200 and the recent performance uplift announcements that came from Nvidia were clearly meant to numb the impact that AMD’s product release would have on its perceived leadership. I don’t imagine we’ll see Nvidia chip sales slowdown because of the MI300X, but rather the AMD part will simply be there to fill in bubbles in the production pipeline with vendors including Microsoft, Dell and Lenovo
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As the size of the data center AI market continues to expand, more areas will open up for AMD to sell out its MI300 chips for the foreseeable future.

Risks to Nvidia, Intel

But this is dangerous for Nvidia over the long term. As more customers use the AMD MI300X and find that it performs well, comes with the software support they need to be successful, and even discover it provides a better performance per dollar, it opens the door for AMD in future generations of AI system integrations.

When the market shortage pulls back, more cloud providers, more system builders and more developers will consider AMD GPUs, when previously they wouldn’t have taken a chance on an unknown. 

Intel has more at risk than Nvidia from the MI300X family simply because this makes AMD the de-facto second source for AI computing in the data center, if it wasn’t already. The efforts for Intel to push into the GPU space have seemingly slowed in recent quarters, with most of the emphasis for CEO Pat Gelsinger and team leaning into the Gaudi AI accelerators that are based on a very different architecture. Intel is hosting its own AI event on December 14^th so we’ll known soon how it plans to address the AI markets in both the data center and PC spaces. 

Ryan Shrout is president of Signal65 and founder at Shrout Research. Follow him on X @ryanshrout. Shrout has provided consulting services for AMD, Qualcomm, Intel, Arm Holdings, Micron Technology, Nvidia and others. Shrout holds shares of Intel.

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