The normal methods of explanation, and the standard definitions, for 'information', such as the 'resolution of uncertainty' are especially difficult to put into practice.
As these presuppose having knowledge already comprised, and/or formed from, a large quantity of information. Such as the concepts of 'uncertainty' and 'resolution'.
How does one know they've truly learned these concepts, necessary for recognizing information, without already understanding the nature of information?
This seems to produce a recursive problem, a.k.a, a 'chicken and egg' problem.
Additionally, the capability to recognize information and differentiate it from random noise must already exist, in order to recognize and understand any definition of information, in fact to understand any sentence at all. So it's a multiply recursive problem.
Since, presumably, most members of this forum can understand sentences, how does this occur?
And since presumably no one could do so at birth, how does this capability arise in the intervening period from birth to adulthood?
I used `` "instance" = category '' notation, which I admit is not necessarily clear. Ok, let me restate to be more clear. "Isn’t minimizing prediction error a form of pattern matching?" Is in my opinion an ill-formed question due to a category (type) mismatch. "Minimizing prediction error" is a particular task, and "pattern matching" is a particular type of algorithms - that is, particular methods one can choose to use to accomplish a task, and "Isn't [a particular task] a form of [methods for accomplishing the task]" are ill-formed because tasks and methods do not have the "a form of" relationship. The relationship they do have is that methods can be suitable (or not suitable) for a particular task, and, depending on a task, multiple different methods might be suitable - as it is indeed the case for the "minimizing prediction error" task.