[mjburgess]

Well.. I think they're over-stated because of the current wave of AI basically only having naïve compression as its tool.

Is the concept `addition` a compression of the space `(Int, Int, Int)` ?

If you want to say it is, OK for some definition of compression. But that compression isnt "mere" in the modern AI sense, it's "exponentially dense".

In that my concept `addition` can generate arbitrarily large amounts of that decompressed space, which is infinite in size.

There's a kind of trick played in the marketing here: since NNs compress, and since learning "can be seen as compression", NNs learn... no, because NNs aren't "exponentially dense", they're "exponentially large" -- I'd claim, the opposite of learning!