Its only equivalent for a very narrow sense of 'prediction' , namely modelling conditional probability distributions over known data.
There's no sense, for example, in which deriving a prediction about the nature of reality from a novel scientific theory is 'compression'
eg., suppose we didn't know a planet existed, and we looked at orbital data. There's no sense in which compressing that data would indicate another planet existed.
It's a great source of confusion that people think AI/ML systems are 'predicting' novel distributions of observations (science), vs., novel observations of the same distribution (statistics).
It should be more obvious that the latter is just compression, since it's just taking a known distribution of data and replacing it with a derivative optimal value.
Science predicts novel distributions based on theories, ie., it says the world is other than we previously supposed.
There's no sense, for example, in which deriving a prediction about the nature of reality from a novel scientific theory is 'compression'
eg., suppose we didn't know a planet existed, and we looked at orbital data. There's no sense in which compressing that data would indicate another planet existed.
It's a great source of confusion that people think AI/ML systems are 'predicting' novel distributions of observations (science), vs., novel observations of the same distribution (statistics).
It should be more obvious that the latter is just compression, since it's just taking a known distribution of data and replacing it with a derivative optimal value.
Science predicts novel distributions based on theories, ie., it says the world is other than we previously supposed.