Nvidia Is Still the King: 1 Clear Reason the Rubin Upgrade Cycle Means the Stock Is Not in a Bubble
Yahoo Finance ·
Since Nvidia ( NVDA 1.86% ) started its monster rise at the beginning of 2023, there have been countless investors who proclaimed the stock to be in a bubble. Time and time again, those investors were proven wrong. There may be a handful of people who are still saying Nvidia is in a bubble right now, although I'd argue that the opposite is true: I think it's undervalued . I think investors are underestimating the potential of the Rubin upgrade cycle that's coming later this year, and it could easily send Nvidia stock to new heights that no stock has ever reached before. Later this year, Nvidia's newest architecture launches. The Rubin chip architectures build upon an already impressive Blackwell architecture, and offer a 10 times reduction in artificial intelligence (AI) inference costs and a four times reduction in training costs. That sounds impressive from a cost-savings standpoint, but what the AI hyperscalers actually hear is that they can achieve a major performance increase at the same cost by running the same number of GPUs.
AI 시장 분석
The article's key point is that Nvidia's Rubin architecture, due at year-end, will cut AI inference costs by 10x and training costs by 4x. Hyperscalers can achieve dramatically higher performance with the same number of GPUs, accelerating data center efficiency and the rollout of AI services. The author argues that NVDA's stock is not a bubble but rather undervalued, forecasting increased demand for GPUs and AI infrastructure. Conversely, competing chips and alternative accelerator vendors may face heightened competitive pressure.
상승 영향
- Semiconductors — Rubin's cost reductions and performance improvements will boost demand for NVDA GPUs and strengthen pricing power, supporting higher semiconductor revenues and margins.
- Data Centers/Cloud — Hyperscalers can obtain higher throughput with the same GPUs or expand new AI services, improving data center utilization and profitability.
- AI Software/SaaS — A sharp drop in inference costs lowers unit economics for LLM- and AI-based services, making productization and scaling easier and benefiting SaaS providers' market expansion and margins.
- Servers/Computing Hardware — Demand for next-generation servers equipped with high-performance GPUs, and for related interconnect and cooling equipment, should rise, benefiting related hardware vendors.
- Memory (HBM) — Expanded GPU-based workloads will drive demand for high-bandwidth memory (HBM), likely increasing shipments and profitability for HBM manufacturers.
하락 영향
- Competing GPU/Chipmakers (AMD, INTC, etc — If Rubin secures a performance and cost advantage, competitors such as AMD and INTC risk losing market share and being disadvantaged in price competition.
- AI accelerator startups and alternative — Standardization around the NVDA ecosystem and its overwhelming efficiency will make it harder for custom ASICs and alternative accelerator startups to differentiate, raising their business risk.
- Traditional CPU-based server solutions — Expansion of GPU-centric workloads could erode demand for existing CPU-based servers, depressing growth for CPU server manufacturers and related software.
AI가 생성한 분석으로 투자 자문이 아닙니다.
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