Gold's Theorem

Gold's Theorem, often related to the field of computational learning theory, states that any function that can be effectively learned by an algorithm must also be learnable by a more general approach called "identification in the limit." Essentially, it highlights that if you have a method to gradually improve your understanding of some concept or function with enough data, there exists a systematic way to learn it completely over time. This underscores the significance of iterative learning and the existence of effective strategies to achieve comprehensive knowledge from incomplete information.