Semiconductors could stay undersupplied for a long time as more capable AI per dollar creates more uses and drives compute demand. Micron and NVIDIA trade at low forward P/Es because investors fear peak cyclical earnings, yet current earnings show no slowdown. Shortages may worsen as AI adoption spreads, though the industry could remain cyclical; a reversal of the forced rollover trade is hoped for, not assured. x.com  x.com  x.com 

A rising value of compute per watt should benefit AI cloud, chip, connectivity and power suppliers. Elon Musk says that value will rise over time. Nebius has Microsoft and Meta deals; Marvell benefits from custom silicon demand; Credo connects GPUs; Vistra has long-term nuclear supply deals with Amazon and Meta; Nokia's Nvidia partnership could help it capture data-center networking growth. x.com  x.com 

AI infrastructure bottlenecks could give eight stocks as much as 18x upside. Nvidia supplies frontier-model GPUs; Broadcom and Marvell supply custom silicon and networking; TSMC makes advanced chips; Micron supplies sold-out HBM; Vertiv provides power and cooling; Palantir monetizes enterprise AI; Alphabet spans TPUs, research, cloud and apps. The list tracks where AI infrastructure spending is flowing. x.com  x.com 

Guaranteeing AI data-center debt could eventually leave Nvidia unable to obtain financing. Per The Information, Nvidia is in talks to provide billions in guarantees on Nscale debt to develop a 460-megawatt data center; one day, its card may read "Denied!" x.com 

Nvidia's AI profits are real, but its compute demand depends heavily on fragile venture funding. Per Chamath, 1% of firms account for 90% of AI spending, and 72 cents of each dollar comes from unprofitable VC-backed firms. Venture money passes through startups to Nvidia and cloud suppliers; if the next raises fail, concentrated orders could contract together. x.com  x.com  x.com 

Nvidia retains pricing power if its full system keeps reducing customers' cost per effective AI task. Strong AI demand alone does not ensure profits across the chain: rising chip, memory and optical costs burden buyers, while tighter financing and slow collections threaten operators. Large customers developing their own chips could pressure Nvidia's margins even as the market grows. x.com 

Nvidia faces risks on both sides of the AI cycle. Vendor financing is a concern at the center of the buildout: strong AI sentiment brings competition, while weaker sentiment brings a slowdown. That makes it the largest holding of greatest concern. x.com 

Nvidia could become the weakest link in AI's circular financing economy as it takes on more customer risk. It is turning to insurers to cover customers' GPU debt, and if insurers require Nvidia to keep backstopping deals, its liabilities will keep growing on top of $245B of supply chain commitments and prepayments as of last quarter. Such large counterparty conflicts are unwise. Amazon is also looking to move $8B of Nvidia Blackwell GPUs into an SPV to take on more debt for its AI buildout. … Show more

Nvidia's system components can reduce the idle time that erodes returns on expensive AI chips. CPUs, accelerator interconnects and server networking help operators such as Nebius and IREN keep machines doing useful work; solving the next bottleneck could win Nvidia more of the data-center equipment budget even when a rival chip looks appealing alone. Buyers must compare the cost of completed work across the whole system. x.com 

Nvidia's ballooning future commitments relative to its revenue evoke Enron. Per Gary Marcus, citing Fortune and Nvidia's 10-Q, second-quarter revenue was $96 billion while future commitments total $366 billion, led by $279 billion of supply and capacity commitments, up from $119 billion a quarter earlier, plus cloud service agreements, data-center leases, equity investments and capex commitments. x.com