Despite intense competition, Amazon's core principle of being 'customer obsessed' means AWS would likely provide Google's TPU chips if key customers demand them. This prioritizes customer retention over platform exclusivity in the AI chip wars.

To counter the competitive threat from Google's TPUs, NVIDIA avoids direct price cuts that would hurt its gross margins. Instead, it offers strategic equity investments to major customers like OpenAI, effectively providing a "partner discount" to secure their business and maintain its dominant market position.

Nvidia's staggering revenue growth and 56% net profit margins are a direct cost to its largest customers (AWS, Google, OpenAI). This incentivizes them to form a defacto alliance to develop and adopt alternative chips to commoditize the accelerator market and reclaim those profits.

Large tech companies are buying up compute from smaller cloud providers not for immediate need, but as a defensive strategy. By hoarding scarce GPU capacity, they prevent competitors from accessing critical resources, effectively cornering the market and stifling innovation from rivals.

While network effects drive consolidation in tech, a powerful counter-force prevents monopolies. Large enterprise customers intentionally support multiple major players (e.g., AWS, GCP, Azure) to avoid vendor lock-in and maintain negotiating power, naturally creating a market with two to three leaders.

Major AI labs aren't just evaluating Google's TPUs for technical merit; they are using the mere threat of adopting a viable alternative to extract significant concessions from Nvidia. This strategic leverage forces Nvidia to offer better pricing, priority access, or other favorable terms to maintain its market dominance.

The high-speed link between AWS and GCP shows companies now prioritize access to the best AI models, regardless of provider. This forces even fierce rivals to partner, as customers build hybrid infrastructures to leverage unique AI capabilities from platforms like Google and OpenAI on Azure.

Beyond capital, Amazon's deal with OpenAI includes a crucial stipulation: OpenAI must use Amazon's proprietary Trainium AI chips. This forces adoption by a leading AI firm, providing a powerful proof point for Trainium as a viable competitor to Nvidia's market-dominant chips and creating a captive customer for Amazon's hardware.

While powerful, Google's TPUs were designed solely for its own data centers. This creates significant adoption friction for external customers, as the hardware is non-standard—from wider racks that may not fit through doors to a verticalized liquid cooling supply chain—demanding extensive facility redesigns.