Simulator Theory (in the context of AI) is an ontology or frame for understanding the working of large generative models, such as the GPT series from OpenAI. Broadly it views these models as simulating a learned distribution with various degrees of fidelity, which in the case of language models trained on a large corpus of text is the mechanics underlying the process that generated that corpus, which may be understood as the people writing, or the dynamics they write about.

It can also refer to an alignment research agenda, that deals with better understanding simulator conditionals, effects of downstream training, alignment-relevant properties such as myopia and agency in the context of language models, and using them as alignment research accelerators. See also: Cyborgism

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