I’m trying to figure out to what extent the character/ground layer distinction is different from the simulacrum/simulator distinction. At some points in your comment you seem to say they are mutually inconsistent, but at other points you seem to say they are just different ways of looking at the same thing.
”The key difference is that in the three-layer model, the ground layer is still part of the model’s “mind” or cognitive architecture, while in simulator theory, the simulator is a bit more analogous to physics—it’s not a mind at all, but rather the rules that minds (and other things) operate under.”
I think this clarifies the difference for me, because as I was reading your post I was thinking: If you think of it as a simulacrum/simulator distinction, I’m not sure that the character and the surface layer can be “in conflict” with the ground layer, because both the surface layer and the character layer are running “on top of” the ground layer, like a windows virtual machine on a linux pc, or like a computer simulation running inside physics. Physical can never be “in conflict” with social phenomena.
But it seems you maybe think that the character layer is actually embedded in the basic cognitive architecture. This would be a distinct claim from simulator theory, and *mutually inconsistent*. But I am unsure this is true, because we know that the ground layer was (1) trained first (so that it’s easier for character training to work by just adjusting some parameters/prior of the ground layer, and (2) trained for much longer than the character layer (admittedly I’m not up to date on how they’re trained, maybe this is no longer true for Claude?), so that it seems hard for the model to have a character layer become separately embedded in the basic architecture.
Taking a more neuroscience rather than psychology analogy: It seems to me more likely that character training is essentially adjusting the prior of the ground layer, but the character is still fully running on top of the ground layer, and the ground layer could still switch to any other character (but it doesn’t because the prior is adjusted so heavily by character-training). e.g. the character is not some separate subnetwork inside the model, but remains a simulated entity running on top of the model.
I’m trying to figure out to what extent the character/ground layer distinction is different from the simulacrum/simulator distinction. At some points in your comment you seem to say they are mutually inconsistent, but at other points you seem to say they are just different ways of looking at the same thing.
”The key difference is that in the three-layer model, the ground layer is still part of the model’s “mind” or cognitive architecture, while in simulator theory, the simulator is a bit more analogous to physics—it’s not a mind at all, but rather the rules that minds (and other things) operate under.”
I think this clarifies the difference for me, because as I was reading your post I was thinking: If you think of it as a simulacrum/simulator distinction, I’m not sure that the character and the surface layer can be “in conflict” with the ground layer, because both the surface layer and the character layer are running “on top of” the ground layer, like a windows virtual machine on a linux pc, or like a computer simulation running inside physics. Physical can never be “in conflict” with social phenomena.
But it seems you maybe think that the character layer is actually embedded in the basic cognitive architecture. This would be a distinct claim from simulator theory, and *mutually inconsistent*. But I am unsure this is true, because we know that the ground layer was (1) trained first (so that it’s easier for character training to work by just adjusting some parameters/prior of the ground layer, and (2) trained for much longer than the character layer (admittedly I’m not up to date on how they’re trained, maybe this is no longer true for Claude?), so that it seems hard for the model to have a character layer become separately embedded in the basic architecture.
Taking a more neuroscience rather than psychology analogy: It seems to me more likely that character training is essentially adjusting the prior of the ground layer, but the character is still fully running on top of the ground layer, and the ground layer could still switch to any other character (but it doesn’t because the prior is adjusted so heavily by character-training). e.g. the character is not some separate subnetwork inside the model, but remains a simulated entity running on top of the model.
Do you disagree with this?