Page StatusAI Transition Model
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Structure2/15
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Summary
This page contains only React component imports with no actual content about AI algorithms, their capabilities, or their implications for AI risk. The page is effectively a placeholder or stub.
Issues1
StructureNo tables or diagrams - consider adding visual content
Algorithms (AI Capabilities)
Algorithmic progress determines how efficiently AI systems convert compute into capabilities. Unlike hardware, algorithms are intangible—discoveries spread instantly through publications, making direct governance nearly impossible.
| Metric | Score | Interpretation |
|---|---|---|
| Changeability | 20/100 | Very difficult to influence |
| X-risk Impact | 75/100 | High direct x-risk impact |
| Trajectory Impact | 85/100 | High long-term effects |
| Uncertainty | 55/100 | Moderate uncertainty |
What Drives Algorithmic Progress?
Causal factors affecting AI algorithmic efficiency. Research shows 91% of gains are scale-dependent (Transformers, Chinchilla), coupling algorithmic progress to compute availability. Software optimizations (23x) dramatically outpace hardware improvements.
Computing layout...
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Scenarios Influenced
| Scenario | Effect | Strength |
|---|---|---|
| AI Takeover | ↑ Increases | strong |
| Human-Caused Catastrophe | ↑ Increases | medium |
| Long-term Lock-in | ↑ Increases | medium |