








Article argues there is no AI infrastructure spending cliff, citing projections of AI infrastructure spend rising from $318B in 2025 to over $1T by 2029. It highlights Alphabet’s $80B equity raise and $180B–$190B capex this year (with higher capex planned for 2027), SpaceX’s accelerating AI-segment capex to a ~$30.8B run rate through March 31, and SK Hynix’s $743B (1,100T won) planned expansion—supportive of sustained Nvidia demand. Overall, it frames Nvidia as well-positioned given 14 straight quarters of sequential revenue growth and continued GPU-centric AI buildouts.
The market is still underestimating how much of the AI capex stack is being pulled forward by non-traditional buyers, which means the near-term winner is not just NVDA but the entire constrained supply chain around HBM, advanced packaging, and networking. The better asymmetry is in suppliers with operating leverage to each incremental rack deployment; NVDA still captures the profit pool, but its upside is increasingly capped by valuation and the probability that some customers eventually internalize more silicon.
The key second-order risk is that hyperscalers can keep spending while still compressing their own free cash flow, so the stock reaction may become more sensitive to spend quality than spend quantity. In the 1-3 month window, reaffirmed capex budgets should keep the tape constructive; in 6-18 months, the issue is mix shift toward custom ASICs and efficiency gains that can slow NVDA’s share of wallet even if total AI spend keeps rising.
The contrarian miss is that the consensus is still debating an AI spending cliff, while the real risk/reward is a more mundane one: margin dilution at the buyers and bottlenecks at the suppliers. If deployment is constrained by power, integration, or memory lead times, the market can keep bidding the narrative without getting the earnings cadence it expects. That argues for relative-value expressions rather than outright chasing beta.
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