The lab studies how intelligence can reason with less noise, less energy, and more structure.

We often assume that making AI closer to human thinking is the benchmark of progress. Yet by blindly copying biological cognitive architectures, we transfer their fundamental vulnerabilities into digital code. Modern LLMs, built on the Attention mechanism, suffer from the same limitations as the human psyche: context overload and attention blur lead to inevitable errors. We are not merely creating intelligence — we are digitizing our own cognitive distortions.

This gives rise to the phenomenon of the "Stupidity Singularity": under conditions of information chaos, models begin to hallucinate, replacing the search for truth with plausible rationalization. The solution to the AI Alignment problem lies not in increasing capacity, but in understanding the physics of these limitations. Our research proposes separating human interfaces (HCA) from machine logic (MCA) to prevent this "cognitive contamination" and preserve the rationality of the artificial agent.