CFPE Methodology v2.0: Cascading Bayesian Foresight Engine with historical back-casting calibration (1976-2026, 1950-2000, 1926-1976).
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Updated
Jul 16, 2026 - Python
CFPE Methodology v2.0: Cascading Bayesian Foresight Engine with historical back-casting calibration (1976-2026, 1950-2000, 1926-1976).
Joules-per-Compute Universal Benchmark (JPCUB): establishing joules-per-solution as the only honest arbiter of computational advantage across CPUs, AI, crypto, quantum, data centers, neuromorphic, and edge/IoT computing.
CFPE program: Cascading Bayesian Foresight Engine -- methodology, paradigm forecast, 100-year forecast. Consolidated program repo -- 3 project repos merged 2026-08-04 (see PROVENANCE.md).
QNFO 100-Year Paradigm Forecast v2.0: Calibrated Bayesian cascade model across 4 eras (2026-2126+). Cascade EV: 6.5% [4-9%].
CFPE Paradigm Forecast: Scenario-tested Bayesian cascade model across 4 eras (2026-2126+). Falsification register, evidence grading, fault-tree decomposition, counterfactual pathways, sensitivity analysis.
Computing After Silicon: A History-Constrained Forecast of Computing Machine Evolution, 2026-2050
Validating JPCUB as a predictive metric for computing paradigm shifts — historical backtest + prospective ranking of post-silicon candidates
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