AI Development Velocity and Governance Simulator

Anthropic Slowdown Call Model • Capability Acceleration vs Safety Boundaries
Governance Presets
Frontier Parameters
Training Compute Scale 1.0e+26 FLOPs
Order of magnitude: 10²³ (GPT-4 era) to 10²⁸ (Hyper-ASI cluster)
Alignment Research Allocation 25%
R&D compute & talent dedicated exclusively to interpretability & safety
External Audit Cadence 6 months
Independent red-teaming and dangerous capability evaluations
Governance Dynamics: Capability advances exponentially with compute, while safety verification exhibits logarithmic scaling unless alignment investments compress the safety gap.
36-Month Horizon Projection
Real-time trajectory modeling capability growth vs governance margin
Capability Index
Safety Capacity
Control Retention %
Critical Boundary
Control Telemetry
Control Retention Score
84.5
Probability of human intent compliance (0-100)
System Risk State
Moderate-Controlled
Governor verified within operational limits
Recommended Action
Safety-Capability Gap
+12.4 index pts
Verification lag at Month 36
Context: Grounded in calls by frontier AI leaders for coordinated pacing. When compute leaps outpace interpretability science, loss-of-control vectors become non-linear.
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