Comment by gnulinux

They are related and the reason is the last point of the OP article: Abstraction. Things can be "physically" deterministic, but can be abstracted as non-deterministic. This seems strange at first but it actually makes a lot of sense, as long as you're not modelling physics itself, it's irrelevant that there is a theory in which your non-model is deterministic. Machine learning algorithms like ChatGPT can be good examples, given the exact same input+random seed, of course, they'll return the same exact output, but the situation is so computationally complex that modeling that system as deterministic is less useful than modelling it as if it's non-deterministic. This is the same way your computer RAM is not "infinite"--it's like trillions of bits-- but in CS we model it as if it's infinite because the practical difference is not the focus of the discussion. If the discussion really was "can we fit a pigeon in every bit of my computer" or "can we manufacture every bit of this RAM in finite amount of time" then yes, it would be relevant to argue that RAM isn't actually infinite. But given that we're interested in models of computation that get exponentially larger and larger as memory grows, even 10 bits can be an intractibly large space (cf. Busy Beaver numbers) so you might as well solve the problem as if it's infinite.