엔비디아를 넘어: AI 다음 단계 시장 선도자의 부상 전망
Beyond Nvidia: Why the Next Phase of AI Could Crown a New Market Leader
LLM 훈련 단계에서 추론 및 에이전트 AI 워크로드로의 시장 전환은 AMD의 칩렛 및 메모리 최적화 우위를 구조적으로 유리하게 만듭니다.
핵심 요약
AI 시장이 LLM 훈련에서 추론 중심으로 전환됨에 따라, AMD는 칩렛 설계와 메모리 최적화 기술을 활용하여 새로운 추론 시장에서 경쟁 우위를 확보할 잠재력이 있습니다.
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Original Article
Beyond Nvidia: Why the Next Phase of AI Could Crown a New Market Leader
Nvidia ( NVDA +3.09% ) was the undisputed chip design champion during the first phase of the AI megatrend, when workloads centered on the training of frontier large language models (LLMs). Its powerful graphics processing units (GPUs) were ideal for this task, and it benefited even more from the wide moat provided by its CUDA software platform , which was where most foundational AI code was written. The chipmaker sold vast numbers of its GPUs, and continues to.
However, in the next phase of the AI trend, the center of gravity is shifting toward inference and agentic AI workloads, and with that, there could be a shift in the marketplace. The big winner of this phase looks like it may be Advanced Micro Devices ( AMD +2.18% ) . While it is highly unlikely to unseat Nvidia as the leader in processors for AI model training or surpass its market cap, AMD's stock looks poised to outperform its larger rival over the next few years.
There are two powerful tailwinds forming that bode well for AMD. The first is the shift toward AI inference -- applying AI to real-world problems -- which is eventually expected to become a much bigger market than LLM training. As an ongoing expense, there is much more emphasis on cost-per-inference, and these processes tend to revolve much more around access to memory than raw compute power. AMD is addressing this in two ways.
First, its chiplet design allows its GPUs to be packaged with more memory than Nvidia's, making them ideal for inference workloads. Meanwhile, it recently acquired memory optimization company MEXT, which will allow it to incorporate its software into complete systems. MEXT's technology uses AI to offload infrequently used data to flash memory and restore it to DRAM just before it is needed, essentially expanding memory capacity virtually without meaningfully impacting performance, and helping reduce costs. AMD already has a few large GPU deals in place, which should help drive tremendous revenue growth.
Image source: The Motley Fool.
In addition to its opportunity in inference, AMD will enjoy another potent growth driver thanks to the coming rise of agentic AI. While prior types of AI workloads had to be handled primarily by powerful parallel processors -- i.e., GPUs and application-specific integrated circuits -- AI agents require more central processing units (CPUs) to handle sequential processes, and as such, the proportion of CPUs to GPUs in data centers optimized for agentic AI will grow meaningfully. Whereas in data centers built for inference, the average ratio recently was around 1 CPU for every 8 GPUs, for agentic AI, Intel predicts that ratio will shift to 1 CPU for 1 GPU.
AMD has long been a leader in high-performance data center CPUs, so that transition opens up a big market opportunity for it. The company has already brought out high-core CPUs designed specifically to handle AI agents, which should position it to continue to gain market share from Intel, which has been its primary rival in that niche.
With AMD riding two of the most powerful trends in AI infrastructure, expect the stock to continue to outperform in the years ahead, and to be a top AI stock to own.