Pre-TAI Capital Deployment: $100B-$300B+ Spending Analysis

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  "title": "Pre-TAI Capital Deployment: $100B-$300B+ Spending Analysis",
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  "llmSummary": "Analysis of how frontier AI labs (Anthropic, OpenAI, Google DeepMind) could deploy \\$100-300B+ before TAI. Compute infrastructure absorbs 50-65% of spending (\\$200-400B+ across the industry), with Stargate alone at \\$500B committed. Safety spending remains at 1-5% (\\$1-15B) representing different allocation choices across labs. Historical analogies (Manhattan Project \\$30B, Apollo \\$200B) provide context for current AI investment levels. Key finding: the spending pattern—and especially the safety allocation—is a variable that other organizations, governments, and funders are actively planning around.",
  "description": "Analytical model examining how frontier AI labs could deploy \\$100-300B+ before transformative AI arrives, covering infrastructure, compute, talent, safety, and implications for other organizations planning around AI lab scaling.",
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      "text": "\\$9B ARR",
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