AMAZON DATACENTER, GPU, EDGE AI

In a discussion featuring Mandeep Singh, Global Head of Technology Research, the focus centers on cloud infrastructure and AI competition among tech giants. While Amazon operates around 32–35 data centers with a $130 million AI revenue run rate—dwarfed by competitors like Microsoft and Google with $5 billion—its limited GPU capacity explains its smaller AI backlog. The need for geographically distributed edge data centers is emphasized to minimize latency when serving massive LLMs to billions of global users, not just to house compute power. Google is highlighted as a leader due to its advanced seventh-gen TPUs, energy-efficient AI chips, and unique advantage of owning a real-time search index, which grounds its Gemini models and reduces hallucinations. Meanwhile, Amazon’s aggressive land acquisition for data centers is creating a “land grab” that squeezes out newer “neo cloud” players. Finally, OpenAI is expected to shift toward product- and application-focused strategies, especially in e-commerce, to challenge Google’s ad revenues and Amazon’s marketplace dominance.

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