<ul data-eligibleForWebStory="false"><li>A researcher developed the Garrett Physical Model (GPM) to understand how meaning collapses, observers interact with symbolic fields, and recursive interpretation in language models.</li><li>The GPM includes elements like interpretive state, symbolic change, recursive operator, halting condition, and interpretive field, explaining how systems collapse when recursive interpretation exceeds containment limits.</li><li>Experiments using symbolic artifacts A and B on various AI platforms like ChatGPT, Claude, Gemini, and Grok showed model-aligned responses, demonstrating recursive reasoning, correct identification of halting conditions, and termination behavior as predicted by the model.</li><li>The independent researcher behind the model has no formal training in physics but developed and tested the model publicly, suggesting it could explain language model behavior in recursive settings and potentially apply to the physical world as well.</li></ul>

I Built and Tested a New Model of How the Universe — and Language Models — Work

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