Chaos does not make prediction impossible, it makes it expensive in a specific way. Errors here grow multiplicatively: the gap between two nearly identical runs doubles every so often, on a timescale set by the system rather than by you. That means the horizon you can predict to grows like the logarithm of your precision. Measuring the initial state ten times more accurately buys you only about 3.3 extra doubling times, and doing it a thousand times better buys about 10. Every further digit costs as much as the last one and returns the same small increment. That is why weather forecasts stall around two weeks no matter how many sensors are added.