What are simulacra?
“Physically”, they’re strings of text output by a language model. But when we talk about simulacra, we often mean a particular character, e.g. simulated Yudkowsky. Yudkowsky manifests through the vehicle of text outputted by GPT, but we might say that the Yudkowsky simulacrum terminates if the scene changes and he’s not in the next scene, even though the text continues. So simulacra are also used to carve the output text into salient objects.
Essentially, simulacra are to a simulator as “things” are to physics in the real world. “Things” are a superposable type – the entire universe is a thing, a person is a thing, a component of a person is a thing, and two people are a thing. And likewise, “simulacra” are superposable in the simulator, Things are made of things. Technically, a random collection of atoms sampled randomly from the universe is a thing, but there’s usually no reason to pay attention to such a collection over any other. Some things (like a person) are meaningful partitions of the world (e.g. in the sense of having explanatory/predictive power as an object in an ontology). We assign names to meaningful partitions (individuals and categories).
Like things, simulacra are probabilistically generated by the laws of physics (the simulator), but have properties that are arbitrary with respect to it, contingent on the initial prompt and random sampling (splitting of the timeline). They are not necessary but contingent truths; they are particular realizations of the potential of the simulator, a branch of the implicit multiverse. In a GPT simulation and in reality, the fact that there are three (and not four or two) people in a room at time is not necessitated by the laws of physics, but contingent on the probabilistic evolution of the previous state that is contingent on (…) an initial seed(prompt) generated by an unknown source that may itself have arbitrary properties.
We experience all action (intelligence, agency, etc) contained in the potential of the simulator through particular simulacra, just like we never experience the laws of physics directly, only through things generated by the laws of physics. We are liable to accidentally ascribe properties of contingent things to the underlying laws of the universe, leading us to conclude that light is made of particles that deflect like macroscopic objects, or that rivers and celestial bodies are agents like people.
Just as it is wrong to conclude after meeting a single person who is bad at math that the laws of physics only allow people who are bad at math, it is wrong to conclude things about GPT’s global/potential capabilities from the capabilities demonstrated by a simulacrum conditioned on a single prompt. Individual simulacra may be stupid (the simulator simulates them as stupid), lying (the simulator simulates them as deceptive), sarcastic, not trying, or defective (the prompt fails to induce capable behavior for reasons other than the simulator “intentionally” nerfing the simulacrum – e.g. a prompt with a contrived style that GPT doesn’t “intuit”, a few-shot prompt with irrelevant correlations). A different prompt without these shortcomings may induce a much more capable simulacrum.