Cross-Branch Comparison

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For 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
229_001229_002229_007229_011229_012230_013231_013231_021231_026231_041231_050232_017232_018232_019232_055232_060233_007233_016235_012236_030236_033237_025238_018238_021238_023238_025238_032 (selected)238_064239_003239_005
FamilyAllCompute scaleEnergy / gridHumanoid deploymentRobotaxiAGIASI$1T+ IPOMars uncrewedAI pauseRecession
238_032
End-state of AI is abundance and post-scarce labor — path is 'no firewall'
Labor/Jobs · Alex Wissner-Gross · conv 5/5 · resolves 2029-03
live posterior: 40% (prior 55%)
Scenario range
0.1pp
34% to 34% across 4 scenarios
cache 37 rows · 2026-05-24 04:31 UTC
cf:e20a3cc6aed2

Humanoid deployment

cumulative — branches can co-occur · range 0.1pp
ScenarioScenario probP(238_032 | scenario)Δ live
S_HUMANOID_FACTORY_2026
Humanoid R1: 10K+ factory units by Nov 2026
40%
34%
-6pp
S_HUMANOID_ENTERPRISE_2028
Humanoid R2: 100K+ enterprise by Nov 2028
50%
34%
-6pp
S_HUMANOID_CONSUMER_2030
Humanoid R3: 1M+ consumer by Nov 2030
20%
34%
-6pp
S_HUMANOID_MASS_2033
Humanoid R4: 10M+ cumulative by Dec 2033
10%
34%
-6pp

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.