Adaptive Entangled Game Modules in Artificial General Intelligence
Stock traders act like entangled quantum systems, not rational individuals
Researchers analyzing Chinese stock market trading found that 89% of trader decisions follow patterns predicted by a quantum-inspired model of interconnected, adaptive agents—far more than the less than 5% explained by traditional finance's assumption of independent rational actors. Traders also show sudden shifts in their decision-making when exposed to news and events, suggesting their brains operate through entangled mechanisms similar to quantum systems rather than through isolated rational calculation.
Financial forecasting has relied for decades on models assuming traders act independently and rationally, which consistently fail to predict real market behavior. This research suggests that AI systems trained on quantum-inspired brain models could predict market movements and trader behavior far more accurately than current systems, potentially improving everything from trading algorithms to risk management and policy design. It also points toward building artificial intelligence that mimics how human brains actually work—through interconnected adaptive systems—rather than through brute-force neural networks that require trillions of hidden parameters.