- Monte Carlo analysis
- Monte Carlo analysis (aggressive)
- Parameter importance analysis
- Timelines analysis
Here, you will find the distributions of results that come from sampling the parameters according to Tom Davidson's beliefs. The median training requirements for AGI are ~1e36 FLOP using 2022 algorithms.
Probability of full economic automation before 2100 : 89%
Probability of slow takeoff : 74%
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| Quantile | Powerful sub-AGI year | AGI year | 20% automation year | 100% automation year | 20% R&D automation year | 100% R&D automation year | Wake-up year | 20-100% economic automation | 20-100% R&D automation | Powerful sub-AGI to AGI | 2X to 10X cognitive output multiplier | 5% to 20% GWP growth |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.01 | 2024.0 | 2025.2 | 2024.8 | 2025.7 | 2024.2 | 2025.6 | 2024.0 | 0.3 | 0.9 | 0.1 | 0.4 | 0.4 |
| 0.10 | 2026.9 | 2029.1 | 2027.7 | 2029.6 | 2026.8 | 2029.4 | 2026.6 | 0.8 | 1.6 | 0.4 | 0.7 | 0.7 |
| 0.20 | 2029.5 | 2032.2 | 2030.0 | 2032.7 | 2028.9 | 2032.4 | 2028.7 | 1.2 | 2.2 | 0.9 | 1.0 | 1.0 |
| 0.50 | 2038.8 | 2043.2 | 2038.3 | 2043.3 | 2036.7 | 2042.9 | 2036.6 | 2.9 | 4.3 | 2.4 | 2.1 | 2.4 |
| 0.80 | 2062.3 | 2070.6 | 2058.8 | 2070.3 | 2055.5 | 2069.7 | 2055.3 | 7.6 | 9.6 | 6.5 | 5.3 | 6.6 |
| 0.90 | 2095.0 | ≥ 2100 | 2088.2 | ≥ 2100 | 2082.2 | ≥ 2100 | 2083.1 | 12.5 | 14.6 | 10.9 | 8.6 | 12.2 |
| 0.99 | ≥ 2100 | ≥ 2100 | ≥ 2100 | ≥ 2100 | ≥ 2100 | ≥ 2100 | ≥ 2100 | 28.0 | 30.7 | 27.0 | 18.5 | 30.7 |
| mean | 2047.3 | 2051.4 | 2046.5 | 2051.5 | 2044.6 | 2051.2 | 2044.6 | 5.1 | 6.5 | 4.3 | 3.6 | 4.7 |
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