Google's strategy isn't just to sell AI chips; it's a platform play. By offering its powerful and potentially cheaper TPUs to companies, Google can create a powerful incentive for those customers to run their entire AI workloads on Google Cloud, creating a sticky, integrated ecosystem that challenges AWS and Azure.

Google is offering its TPUs externally for the first time as a strategic move to gain market share while it has a temporary hardware advantage over Nvidia. This classic tactic aims to build a crucial install base that can be upgraded later, even after its competitive performance edge inevitably narrows.

In a significant strategic misstep, Google sold a large volume of its custom TPU accelerators to rival Anthropic. Immediately after, demand for Google's own Gemini model surged, leaving Google compute-constrained and trying to secure more capacity from a sold-out TSMC.

Google Cloud's impressive growth is attributed to servicing the massive compute needs of Anthropic, a company it heavily invested in. This highlights a circular dynamic where cloud providers fund AI companies, which in turn become their captive, high-margin customers for GPUs and TPUs.

Google is positioned to take market share from OpenAI and Anthropic because its diversified business model does not depend heavily on token revenue. This allows Google to offer the cost controls and predictable pricing that enterprises demand, potentially using its AI models as a loss leader to drive cloud adoption.

DeepMind's lack of a dedicated CEO or financial reporting unit reveals Google's core AI strategy: treat it as a cross-organizational layer to be "vended" into existing products like Search and Docs. While this promotes integration, it may also prevent the focused, singular drive needed to compete with standalone AI companies, explaining why they often feel behind despite their capabilities.

Cloud providers like Amazon and Google benefit regardless of which AI model wins. By structuring deals as large-scale compute commitments in exchange for equity (e.g., with Anthropic), they profit from cloud usage fees, drive adoption of their in-house silicon, and gain visibility into data center capex recovery, effectively hedging their bets across the entire AI ecosystem.

Google's cloud division (GCP), incentivized to sell compute, is allocating scarce TPU chips to external customer Anthropic. This directly constrains Google's own AI lab, Gemini, hindering its progress in the hyper-competitive AI race and revealing significant internal friction between business units with conflicting goals.

As the current low-cost producer of AI tokens via its custom TPUs, Google's rational strategy is to operate at low or even negative margins. This "sucks the economic oxygen out of the AI ecosystem," making it difficult for capital-dependent competitors to justify their high costs and raise new funding rounds.