If AI is truly transformational, its greatest long-term value will accrue to non-tech companies that adopt it to improve productivity. Historical tech cycles show that after an initial boom, the producers of a new technology are eventually outperformed by its adopters across the wider economy.

Google training its top model, Gemini 3 Pro, on its own TPUs demonstrates a viable alternative to NVIDIA's chips. However, because Google does not sell its TPUs, NVIDIA remains the only seller for every other company, effectively maintaining monopoly pricing power over the rest of the market.

Even if Google's TPU doesn't win significant market share, its existence as a viable alternative gives large customers like OpenAI critical leverage. The mere threat of switching to TPUs forces NVIDIA to offer more favorable terms, such as discounts or strategic equity investments, effectively capping its pricing power.

Massive AI capital expenditures by firms like Google and Meta are driven by a game-theoretic need to not fall behind. While rational for any single company to protect its turf, this dynamic forces all to invest, eroding collective profitability for shareholders across the sector.

This theory suggests Google's refusal to sell TPUs is a strategic move to maintain a high market price for AI inference. By allowing NVIDIA's expensive GPUs to set the benchmark, Google can profit from its own lower-cost TPU-based inference services on GCP.

Swisher draws a direct parallel between NVIDIA and Cisco. While NVIDIA is profitable selling AI chips, its customers are not. She predicts major tech players will develop their own chips, eroding NVIDIA's unsustainable valuation, just as the market for routers consolidated and crashed Cisco's stock.

While OpenAI leads in AI buzz, Google's true advantage is its established ecosystem of Chrome, Search, Android, and Cloud. Newcomers like OpenAI aspire to build this integrated powerhouse, but Google already is one, making its business far more resilient even if its own AI stumbles.

The narrative of a broad AI investment boom is misleading. 60% of the incremental CapEx dollars in the first half of 2025 came from just four firms: Amazon, Meta, Alphabet, and Microsoft. Owning or being underweight these four stocks is a highly specific bet on the capital cycle of AI.

The narrative of endless demand for NVIDIA's high-end GPUs is flawed. It will be cracked by two forces: the shift of AI inference to on-device flash memory, reducing cloud reliance, and Google's ability to give away its increasingly powerful Gemini AI for free, undercutting the revenue models that fuel GPU demand.