There’s a compelling hypothesis in the field of machine learning called ‘overfitting,’ where systems become so tuned to recognizing patterns that they falter when faced with new, unexpected scenarios. Interestingly, some computer scientists are exploring ways to inject noise into computational models to keep them adaptable.