I think we in perfect agreement here. Like I said in my comment, we can accurately describe the shape of noise, and that’s incredibly useful for making predicti

I think we in perfect agreement here. Like I said in my comment, we can accurately describe the shape of noise, and that’s incredibly useful for making predictions. But we can’t make absolute deterministic predictions within the noise. I.e. we can say thing X has a 90% probability of happening. But we can’t say thing X will happen. And of course a strong probabilistic prediction is incredibly powerful and useful. I don’t want to suggest that it isn't, but it’s not an absolute prediction. And once again usefulness of a probabilistic prediction is almost always as useful as an absolute prediction (I would also argue that absolute prediction don’t really exist in the real world, they’re just extremely high confidence probabilistic predictions, but you haven’t bothered to model the actual noise).