Future Studies
THE SCIENCE OF SEEING WHAT HASN'T HAPPENED YET
A constraint-graph simulation engine that models physical supply chains, simulates forward through known transfer functions, identifies binding bottlenecks the market hasn't priced, and scores every prediction against reality.
CONCEPTS
01 // Why We Can't See the Future
Cognitive biases, architectural failure, and the prediction problem
02 // A Brief History of Forecasting
From Delphi to ensemble weather prediction
03 // The Tetlock Revolution
28,361 predictions and the fox-hedgehog distinction
SYSTEMS
04 // 49 Petaflops of Future-Seeing
Weather prediction — the template for everything that works
05 // Renaissance Technologies
Statistical prophecy and the inference ceiling
06 // Prediction Markets
The wisdom and madness of crowds
07 // Digital Twins
Simulating Earth at kilometer resolution
08 // Agent-Based Simulation
Six archetypes, emergent market dynamics
RESEARCH
09 // The Superforecasters
Fermi decomposition and the prediction-as-skill hypothesis
10 // From Inference to Simulation
The architectural gap that no one has filled
11 // Constraint Graph Architecture
Nodes, edges, Monte Carlo forward simulation
12 // Capital Cycles
Marathon Asset Management's supply-side framework
13 // Adversarial Falsification
Every prediction gets kill conditions
14 // Bayesian Updating in Practice
The mathematics of learning from experience
15 // Temporal Confidence Tracking
Decomposed Brier scores and the meta-learning signal
16 // The Uranium Fuel Cycle
A complete worked example with real numbers
FRONTIERS
17 // Chaos, Black Swans, and Irreducible Uncertainty
The hard limits of prediction
18 // The Calibration Problem
When you say 70 percent, does it happen 70 percent of the time?
19 // Keeping Score
Brier scores and Murphy's decomposition
20 // Prediction vs Prophecy
Why prediction scales and prophecy doesn't
REFERENCES
Bibliography
Master citation index across all articles