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.

The competition for AI dominance has moved beyond chips to securing massive energy and infrastructure. Anthropic's new deal with Google for 3.5 gigawatts of power capacity highlights this shift. This single deal effectively created a multi-billion dollar business for Google, reframing the AI race as a battle for power plants.

Major cloud providers like Amazon are making multi-billion dollar investments in AI startups like Anthropic, which then commit to spending that money back on the provider's cloud services. This "circular" financial arrangement locks in future revenue and inflates growth metrics with non-organic activity.

Top AI labs like Anthropic are simultaneously taking massive investments from direct competitors like Microsoft, NVIDIA, Google, and Amazon. This creates a confusing web of reciprocal deals for capital and cloud compute, blurring traditional competitive lines and creating complex interdependencies.

Anthropic is pioneering a new hardware strategy. Instead of just renting Tensor Processing Units (TPUs) from Google Cloud, it is buying the chips directly from co-designer Broadcom. This gives Anthropic more control over its infrastructure, a significant move away from the standard cloud-centric model for AI companies.

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.

For leading AI labs like Anthropic and OpenAI, the primary value from cloud partnerships isn't a sales channel but guaranteed access to scarce compute and GPUs. This turns negotiations into a complex, symbiotic bundle covering hardware access, cloud credits, and revenue sharing, where hardware is the most critical component.

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.

Google Cloud's growth is dramatically outpacing rivals, fueled by a 400% year-over-year increase in its backlog. The key is its integrated model, selling its entire AI stack from custom TPU infrastructure to Gemini apps. This full-stack approach is resonating strongly with enterprise customers.