Multi-Actor Strategic Landscape

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  "summary": "Analyzes AI risk through the lens of which actors develop TAI, finding actor identity may account for 40-60% of total risk variance, with detailed quantitative data on US-China capability convergence (benchmark gap narrowed from 9.26% to 1.70% in ~13 months), investment asymmetries (\\$222B US vs \\$98B China VC), and four risk pathways summing to ~25% combined x-risk. The framework is well-populated with 2025-2026 data but the core model parameters (risk estimates, variance attribution) are explicitly acknowledged as illustrative rather than empirically derived.",
  "description": "Analyzes how AI risk varies by which actors develop TAI, finding actor identity may determine 40-60% of total risk variance. Updated with 2025-2026 investment asymmetries, near-parity capability data, and governance spend estimates.",
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      "text": "Stephen McAleese, LessWrong, January 2025",
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