Cross-Branch Comparison
cache age 350h 17mFor a single prediction, see its conditional probability across every scenario branch. Predictions whose probability varies widely are "scenario-sensitive" — the position is a leveraged bet on which future fires. Flat rows = robust to scenario uncertainty.
Pick a prediction
High-conviction (≥4) predictions with ≥2 ticker exposures
238_021
Math, science, engineering, and medicine will all be solved by AI
AI · Alex Wissner-Gross · conv 5/5 · resolves 2029-03
live posterior: 42% (prior 55%)
Scenario range
13.4pp
29% to 42% across 4 scenarios
cache 37 rows · 2026-05-24 04:31 UTC
cf:e20a3cc6aed2
AGI
mutually exclusive — exactly one branch fires · range 13.4pp
| Scenario | Scenario prob | P(238_021 | scenario) | Δ live |
|---|---|---|---|
S_AGI_FAST_2027 AGI fast: drop-in remote worker by 2027-09 | 30% | 29% | -13pp |
S_AGI_MID_2029 AGI mid: Kurzweil 2029 path | 35% | 42% | +0pp |
S_AGI_SLOW_2031 AGI slow: Schmidt/Hassabis 5-10 year path | 25% | 29% | -13pp |
S_AGI_WINTER_2036PLUS AGI delayed: capability plateau or AI winter | 10% | 29% | -13pp |
What this tells you
- High sensitivity (≥30pp range): this claim's probability swings wildly depending on which future fires. Sizing should be smaller; pair with a hedge that has the opposite sensitivity profile.
- Flat row (≤10pp range): the claim is robust — same probability in good and bad scenarios. A "no-regret" position; you don't need to time the underlying scenario.
- Spike on one branch: a leveraged thesis on a specific scenario. If that scenario's prior shifts, this position re-rates massively.