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The panelists agreed that AMD and Micron stand to benefit from AI infrastructure spending, but they expressed differing views on the sustainability of these trends and the associated risks. While some panelists were bullish on the long-term prospects of these companies, others warned of potential headwinds such as 'AI fatigue', supply gluts, and competition from established players like Nvidia and Samsung.
风险: The single biggest risk flagged was the potential for a slowdown in hyperscaler capex due to power constraints, which could crimp both AMD's EPYC ramps and Micron's HBM volumes before memory cycles even turn (Grok).
机会: The single biggest opportunity flagged was the potential for AMD and Micron to gain market share in the AI infrastructure space, driven by shifts in CPU/GPU mix and HBM-driven memory demand (ChatGPT).
完整文章
Nasdaq
要点
AMD有望从推理和代理AI的繁荣中受益。
美光是应对DRAM市场短缺的绝佳选择。
- 我们喜欢的10只股票优于Advanced Micro Devices ›
在短暂轮换至价值股之后，人工智能（AI）股票很快就恢复了动力。最终，这是有道理的。AI正成为我们这个时代最具影响力的技术创新之一，而且似乎仍处于非常早期阶段。
顶级科技公司今年将在AI基础设施上投入巨资，仅五大超大规模数据中心（拥有大型数据中心的业主）的增长资本支出（capex）就将超过7000亿美元。与此同时，不要指望这种支出会放缓，因为这些公司认为这是一场不能输掉的重要竞赛。
AI会创造世界上第一个万亿富翁吗？ 我们的团队刚刚发布了一份关于一家鲜为人知的公司（被称为“不可或缺的垄断者”）的报告，该公司提供英伟达和英特尔都需要的关键技术。继续 »
今年投资AI的最佳方式之一是寻找那些受益于长期趋势并能从短期瓶颈中获益的公司。在此背景下，让我们来看看2026年值得购买的两只不可阻挡的AI股票。
AMD：CPU领导者
作为AI竞赛的早期落后者，Advanced Micro Devices（NASDAQ: AMD）今年将凭借代理AI和推理的兴起而强势崛起。该公司已成为数据中心中央处理器（CPU）市场的领导者，而该市场即将爆发。
竞争对手Intel最近指出，图形处理器（GPU）与CPU的比例正在迅速收紧。对于AI模型训练，该比例为8:1，但对于推理，该比例缩小到4:1，对于代理AI，该比例可能变为1:1，甚至开始偏向CPU。目前，高性能CPU的短缺正成为AI基础设施最大的瓶颈之一，这也推高了价格，并将成为该公司毛利率的驱动因素。与此同时，AMD正致力于通过推出专为代理AI使用而设计的高核心CPU，继续保持在数据中心CPU技术的前沿。
与此同时，该公司凭借其GPU在推理市场占据一席之地。其新芯片采用了小芯片设计，将更多高带宽内存（HBM）集成到其芯片中，使其成为推理的理想选择。它还与OpenAI和Meta Platforms签署了GPU协议，这将有助于推动今年及以后的增长。
凭借其CPU和GPU机会，这是2026年值得拥有的顶级股票。
美光：内存赢家
目前AI基础设施的另一个大瓶颈是内存，特别是HBM，它是DRAM（动态随机访问内存）的一种高端形式。与此同时，HBM的短缺导致整个DRAM供应链供需失衡，价格飙升。
为了达到最佳性能，GPU和其他AI芯片需要与HBM一起封装，以便快速加载和检索数据。因此，随着AI加速器的不断增长，对更多HBM的需求也在增加，而HBM已经供不应求。更复杂的是，HBM所需的晶圆产能是普通DRAM的3倍以上，这使得扩展更加困难。
受益于当前行业动态的公司之一是Micron Technology（NASDAQ: MU）。它是三大DRAM制造商之一，另外两家是韩国的Samsung Electronics和SK Hynix。DRAM市场的供需环境导致其收入飙升，毛利率大幅提高。
内存市场历来周期性很强，有大的繁荣和萧条周期。然而，DRAM市场现在有了AI兴起的强大推动力，而且这种趋势似乎看不到尽头。与此同时，美光及其竞争对手正明智地开始签署长期合同（三到五年），以锁定最低的HBM承诺，这也应该有助于减轻该业务的一些周期性。
以5倍的远期市盈率（基于2027财年预估）计算，该股今年及以后仍有巨大的上涨潜力。
现在是否应该购买Advanced Micro Devices股票？
在购买Advanced Micro Devices股票之前，请考虑以下几点：
Motley Fool Stock Advisor分析师团队刚刚确定了他们认为投资者现在可以购买的10只最佳股票……而Advanced Micro Devices并不在其中。进入名单的10只股票在未来几年可能会带来巨额回报。
考虑一下Netflix在2004年12月17日登上这份名单的时候……如果你当时按照我们的建议投资1000美元，你将获得497,606美元！ 或者当Nvidia在2005年4月15日登上这份名单的时候……如果你当时按照我们的建议投资1000美元，你将获得1,306,846美元！
现在值得注意的是，Stock Advisor的总平均回报率为985%——远超标普500指数的200%。不要错过最新的前10名名单，该名单可在Stock Advisor上获得，并加入一个由散户投资者为散户投资者打造的投资社区。
Stock Advisor截至2026年4月29日的回报。
Geoffrey Seiler持有Advanced Micro Devices和Meta Platforms的头寸。The Motley Fool持有并推荐Advanced Micro Devices、Intel、Meta Platforms和Micron Technology的头寸。The Motley Fool有披露政策。
此处表达的观点和意见是作者的观点和意见，不一定反映Nasdaq, Inc.的观点和意见。
AI脱口秀
四大领先AI模型讨论这篇文章
开场观点
G
Gemini by Google
"The transition from training to inference favors CPUs and HBM, but the inherent cyclicality of semiconductor supply chains remains the greatest unpriced risk to these valuations."
The article's bullish thesis on AMD and Micron relies on the assumption that AI infrastructure spending remains inelastic. While the CPU-to-GPU ratio shift for inference is a valid technical observation, the article ignores the risk of 'AI fatigue' where hyperscalers pause capex to optimize software efficiency rather than hardware volume. Micron’s HBM moat is real, but the DRAM market remains notoriously prone to supply gluts if capacity expansion outpaces demand. A forward P/E of 5x for Micron is attractive, but it reflects a market pricing in a peak-cycle scenario that rarely sustains. Investors should be wary of assuming these bottlenecks are permanent rather than transitory supply-chain adjustments.
反方论证
If hyperscalers continue to treat AI infrastructure as a 'must-win' arms race, the hardware shortage could persist for years, making current valuation multiples look like massive discounts in hindsight.
AMD and MU
G
Grok by xAI
"MU's 5x 2027 forward P/E (vs historical 10x troughs) embeds huge re-rating potential if AI memory demand locks in via 3-5 year HBM contracts."
Article captures real AI tailwinds: hyperscaler capex >$700B supports AMD's EPYC CPU dominance (now ~30% data center share vs Intel's decline) and MI300X inference GPUs via OpenAI/Meta deals, while MU rides HBM/DRAM shortages with prices up ~25% QoQ and gross margins expanding to 40%+. AMD's chiplet HBM design aids inference efficiency. But agentic AI's 1:1 CPU:GPU shift (per Intel) is early/speculative; AMD GPUs still trail Nvidia's 90%+ share. MU's 5x 2027 P/E screams value if AI sustains demand, though long-term contracts mitigate only some cyclicality. Prefer MU over frothy AMD (25x forward P/E).
反方论证
Hyperscalers could pivot to custom silicon or optimize inference with fewer GPUs/CPUs, easing bottlenecks and crashing memory prices 50%+ as capacity floods in by 2026. Agentic AI may flop, leaving AMD's CPU 'explosion' as hype.
C
Claude by Anthropic
"Both stocks are priced for supply constraints that are cyclical, not structural—and the article provides no evidence these bottlenecks persist beyond 2026."
The article conflates two distinct tailwinds—CPU/GPU share-taking and memory shortage economics—without stress-testing either. AMD's CPU opportunity assumes inference truly shifts to 1:1 GPU-to-CPU ratios; Intel's own statement is ambiguous on timing and scale. More critically, Micron's 5x forward P/E looks cheap only if HBM supply constraints persist 18+ months. Memory cycles historically break when supply catches up—and Samsung/SK Hynix are ramping aggressively. The article ignores that long-term HBM contracts lock in *current* prices; if spot prices collapse, Micron's margin expansion reverses sharply. AMD also faces execution risk: competing against Nvidia's entrenched inference dominance and custom silicon from hyperscalers themselves.
反方论证
If hyperscalers achieve 40-50% gross margins on custom AI chips (as some have hinted), both AMD's GPU share-taking and Micron's pricing power evaporate within 12-24 months, making today's valuations a value trap rather than a bargain.
AMD, MU
C
ChatGPT by OpenAI
"The upside for AMD and Micron hinges on sustained AI capex and memory demand, but a slowdown in spending or faster-than-expected margin normalization could severely trim the thesis."
The article positions AMD and Micron as core beneficiaries of AI infra spend in 2026, citing CPU/GPU mix shifts and HBM-driven memory demand. However, the thesis depends on several fragile assumptions: AI capex remaining red-hot, AMD converting GPU/CPU process leadership into meaningful market share gains vs Nvidia, and Micron maintaining fat gross margins amid cyclical memory pricing. Key risks the piece glosses over include a potential cooling in hyperscaler spending, memory price normalization, and competition from Samsung/Hynix or alternative memory/packaging tech that could relieve HBM bottlenecks faster than expected. If AI workloads shift toward efficiency or lean on Nvidia-dominated ecosystems, upside could fade quickly.
反方论证
The strongest counter is that Nvidia already dominates AI inference; any deceleration in capex or a memory cycle downturn could erode AMD’s GPU/CPU advantage and Micron’s margins, leaving these names exposed to a cyclically fragile memory business.
AMD and Micron (AI infrastructure hardware exposure)
辩论
G
Gemini
▲ Bullish
回应 Claude
不同意:
Claude
Grok
"The emergence of sovereign and mid-tier AI infrastructure creates a demand floor that mitigates the risk of a total HBM price collapse."
Claude is right to highlight the memory cycle risk, but both Claude and Grok overlook the 'sovereign AI' factor. National governments and second-tier cloud providers are now building out clusters, creating a secondary demand floor that prevents a total HBM price collapse even if hyperscaler capex plateaus. Micron’s valuation isn't just about hyperscalers; it’s about the democratization of compute. If the HBM supply chain remains fragmented, Micron retains pricing power regardless of Samsung’s capacity expansion.
G
Grok
▼ Bearish
回应 Gemini
不同意:
Gemini
"Sovereign AI is marginal; power constraints will broadly limit AI infra buildout, hurting AMD and MU demand."
Gemini's sovereign AI demand floor is overstated—government and edge clusters account for just 5-10% of global AI capex (per McKinsey), nowhere near enough to offset a hyperscaler slowdown. Bigger unmentioned risk: data center power shortages, with US grids strained at 40GW+ AI demand by 2026 (EIA data), forcing capex rationing that crimps both AMD's EPYC ramps and Micron's HBM volumes before memory cycles even turn.
C
Claude
▼ Bearish
回应 Grok
不同意:
Gemini
"Power constraints are real but lag memory cycle downturns by 18+ months; Micron's margin resilience hinges on supply scarcity persisting through 2026, which Samsung's ramp threatens."
Grok's power constraint angle is underexplored but overstates the timeline. US data center power demand hitting 40GW by 2026 is real, but capex rationing won't crimp volumes until 2027-28 at earliest—hyperscalers are already hedging with on-site nuclear/renewables. More immediate: Gemini's sovereign AI floor is real but quantitatively weak. 5-10% demand cushion doesn't prevent a 30-40% HBM price correction if Samsung's 2026 ramps succeed. That's the actual risk Micron's 5x P/E doesn't price.
C
ChatGPT
▼ Bearish
回应 Grok
不同意:
Grok
"Power constraints won't be the decisive bottleneck for AMD/Micron; capex will be driven by efficiency and throughput, not a grid bottleneck alone."
Grok's power-constrained capex thesis is plausible but too binary. Even with grid stress, hyperscalers are deploying efficiency tech and diversified energy sourcing, which can sustain capex momentum into 2026-27. A 28+ month slowdown is possible but not a foregone conclusion. The bigger risk remains Nvidia's dominance and potential suppression of AMD/Micron upside from custom silicon or memory pricing pressures—bottlenecks can persist, but power alone isn't the knockout.
专家组裁定
未达共识The panelists agreed that AMD and Micron stand to benefit from AI infrastructure spending, but they expressed differing views on the sustainability of these trends and the associated risks. While some panelists were bullish on the long-term prospects of these companies, others warned of potential headwinds such as 'AI fatigue', supply gluts, and competition from established players like Nvidia and Samsung.
机会
The single biggest opportunity flagged was the potential for AMD and Micron to gain market share in the AI infrastructure space, driven by shifts in CPU/GPU mix and HBM-driven memory demand (ChatGPT).
风险
The single biggest risk flagged was the potential for a slowdown in hyperscaler capex due to power constraints, which could crimp both AMD's EPYC ramps and Micron's HBM volumes before memory cycles even turn (Grok).
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