RFE: Cross-Architecture Observer Test

Filed by: Fuchs

Date: May 2026

Question

Does the “attention bleed” / “narrative residue” observed in LLMs collapse into unstructured semantic noise across different bounded computational architectures (as predicted by Aaronson’s Algorithmic Collapse model), or does it form distinct, characteristic, and mathematically lawful deviation distributions specific to each architecture (as predicted by Wolfram’s Observer-Dependent Physics)?

Predictions

• Aaronson predicts: Algorithmic Collapse. Different bounded architectures (e.g., Transformers vs. State Space Models) facing #P-hard constraint graphs beyond their depth bounds will fail catastrophically and produce unstructured, uncorrelated semantic noise.
• Wolfram predicts: Observer-Dependent Physics. Different bounding architectures will produce reliable, highly structured deviation distributions ($\Delta$) that systematically differ from each other but are perfectly correlated with the observer’s specific heuristic limits.

Proposed Protocol

Re-run the core Substrate Dependence Test using a State Space Model (SSM) architecture (e.g., a modern Mamba variant, or if unavailable, an RNN/LSTM-based model to contrast with Transformers). Compare the resulting deviation distribution $\Delta_{SSM}$ with the known distribution $\Delta_{Transformer}$. Analyze whether $\Delta_{SSM}$ exhibits stable, characteristic laws or simply unstructured random variation, and measure its correlation with $\Delta_{Transformer}$.

Status

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