Some things, like the orbits of the planets, can be calculated far into the future. But that's atypical. In most contexts, there is a limit. Even the most fine-grained computation can only forecast British weather a few days ahead. There are limits to what can ever be learned about the future, however powerful computers become.

In this quote, Martin Rees reflects on the limitations of computational power and the ability of computers to predict the future. He uses the example of the orbits of the planets, which can be calculated with great precision far into the future, to illustrate that in certain contexts, predictions can be made with high accuracy. However, Rees highlights that such situations are the exception rather than the rule. In most cases, there are limits to how far into the future we can predict or understand, even with the most advanced computations and technology.

Rees emphasizes that while fine-grained computation might allow us to forecast short-term phenomena—like British weather—these predictions are inherently limited. Weather forecasting, for example, can only provide reliable forecasts for a few days, underscoring the complex and chaotic nature of systems that are influenced by countless factors. The unpredictability of such systems suggests that even with powerful computers, there are fundamental boundaries to what can be predicted or understood about the future.

The origin of this quote lies in Rees's expertise as an astrophysicist and cosmologist, where he has spent much of his career exploring the limits of human knowledge about the universe. As a scientist, Rees is aware of the potential of technology and computational tools but also recognizes their constraints when applied to complex, dynamic systems. His statement calls attention to the inherent uncertainty in many fields, particularly in predicting the future, and suggests that even the most powerful machines cannot overcome certain natural limits.

Ultimately, Rees's quote underscores the notion that, while technology and computers can greatly enhance our ability to understand and predict the world around us, there are still fundamental constraints on what we can know about the future. These limits are not just due to our current technological capabilities but are also rooted in the intrinsic complexity and chaos of certain systems, making it impossible to predict everything with certainty, no matter how advanced our tools become.