Even if we limit ourselves to simple bounded systems.
If the “simple bounded systems” are, basically, enumerable and the definition of “win” is fixed, F(P) can be a simple lookup table which does always win.
It’s the same thing as saying that given a dataset I can always construct a model with zero error for members of this dataset. That does not mean that the model will perform well on out-of-sample data.
I am also not sure to which degree EY intended this statement to be a “hard”, literal claim.
If the “simple bounded systems” are, basically, enumerable and the definition of “win” is fixed, F(P) can be a simple lookup table which does always win.
It’s the same thing as saying that given a dataset I can always construct a model with zero error for members of this dataset. That does not mean that the model will perform well on out-of-sample data.
I am also not sure to which degree EY intended this statement to be a “hard”, literal claim.