> It seems difficult to claim that the computational process that implements this has any more or less of a gestalt then one multiplying two matrices together. So it's not just the existence of certain representations or computational loops that seems to lead to possessing a gestalt.

I've thought a lot about what is lacking in modern VLMs that preclude consciousness. In my view the difference is that their talk of "self" is a simulacrum of the real thing. Current models are feed forward and so self-talk is driven by some parameter that turns on when the network detects context that possibly references the model, and this parameter drives downstream self-talk. It's a very good simulacrum, but it is a far cry from a model with recurrent self-reference around which the inference process is organized. The richness of the self-model in a hypothetical recurrent network with capabilities of modern LMs is much greater than the parameter on/off representation in feed forward networks.