The article examines whether bearish narratives about Nvidia and the broader generative artificial intelligence ecosystem have played out by late 2025, focusing in particular on Edward Zitron’s “Hater’s Guide” critique. It argues that while structural risks such as questionable returns on investment, circular financing, and extreme capital expenditures remain real, the anticipated crash has not arrived. Instead, the market has shifted from speculative exuberance into an entrenched, industrial phase where hyperscalers and governments treat artificial intelligence compute as strategic infrastructure rather than discretionary software spend. This reframing, the author contends, has allowed Nvidia to reposition itself from a hardware supplier into a provider of sovereign critical infrastructure, making its revenue less sensitive to short term profitability of artificial intelligence applications.
The piece contrasts the core bear claims with Nvidia’s reported financials and operational data through Q3 FY2026. In Q3 FY2026, Nvidia reported revenue of 57.0 billion, up 22% sequentially and 62% year-over-year, with Data Center revenue at 51.2 billion and GAAP gross margins at 73.4%. The author notes that inventory rose to 19.8 billion from 15.0 billion, but emphasizes that 44.2% of this is work-in-process tied to complex Blackwell systems, and that Days Sales Outstanding at 53 days, down from 54 days, does not match a channel-stuffing pattern. The analysis also tackles the “circular” CoreWeave relationship, detailing how billions in debt collateralized by Nvidia GPUs and Nvidia’s own equity stake fueled CoreWeave’s growth to a projected 8 billion in 2025 revenue and a reported 55.6 billion backlog, while concluding this model resembles a leveraged utility with concentrated credit risk rather than a fraudulent revenue loop.
Technical and economic constraints feature prominently, especially around the so-called thermodynamic wall. The article recounts reports that GB200 NVL72 racks drawing over 120 kilowatts (kW) encountered overheating and redesign requirements, but frames the subsequent customer investment in liquid cooling and continued orders as evidence of Nvidia’s moat rather than a breaking point. At the macro level, the “ROI Gap” is quantified via estimates that global AI spending reached 644 billion in 2025 while pure generative artificial intelligence software revenue is only 50-60 billion, reinforcing the claim that the economics are “upside down” even as hyperscalers with roughly ~350B in operating cash flow treat this as a long-term defensive arms race. The article argues that rising “Sovereign AI” deals in countries such as Japan, France, India, and the UAE create a buyer-of-last-resort dynamic that insulates Nvidia from a corporate capex pullback, while competition from AMD and internal silicon at Google, Amazon, and Microsoft remains constrained by Nvidia’s CUDA software moat and system-level integration. The closing assessment likens Nvidia more to a Cisco-like arms dealer with an entrenched position than to a house-of-cards fraud, suggesting any eventual reckoning will hit downstream software valuations before it topples Nvidia’s core business.
