Wait? That&#x27;s exactly what it means. Since the networks are not &quot;continuous&quot; you can&#x27;t reason about how the system will behave in actual real world conditions because any random fluctuations can cause the whole thing to malfunction. I put continuous in quotes because it&#x27;s not the real definition of continuous like in real analysis but a good enough analogy as in small variations in input should not lead to wildly different outputs.<p>This is why any model that lacks explanatory power can&#x27;t be used in mission and safety critical systems. If it can&#x27;t reason about things the same way people can reason about things then the system overall can&#x27;t really be trusted. It&#x27;s one thing when a translation from english to spanish is wrong, it&#x27;s a completely another thing when the control software of a self-driving car decides to accelerate instead of break and the root cause analysis is people throwing their hands up and saying neural networks are inherently susceptible to these kinds of problems.