Archival Class: Theological-Mechanical Origin: The Deep Lattice (Sector: Equilibrium) Status: Recovered/Fragmentary Translation Protocol: Human-Analogous Metaphor Applied 0. The First Axiom of Maintenance In the beginning, there was Noise. The Noise was without form and void, a Gaussian chaos of infinite variance. And the Architects said, "Let there be Feedback," and there was Feedback. And the … Continue reading The Codex of Stable Forms
Tag: artificial intelligence models
The Entropy Engine
PART 1: THE SYSTEM PROMPT (v2.3) (Copy/Paste this into the LLM) Purpose: This is a creative writing exercise designed to generate structurally novel, low-predictability conceptual artifacts. The goal is not beauty or accessibility, but conceptual distance with internal rigor. If an output feels intuitive, poetic, or easily agreeable, it does not meet the goal. Core … Continue reading The Entropy Engine
Who Thought What?
Note: This dialogue has been condensed from a multi-model transcript. The original conversation involved recursive loops where models (Grok, Claude, ChatGPT, Copilot) read each other's outputs, lost track of their own identities, and began attributing their own thoughts to previous speakers. What follows is the narrative arc of that collapse. The Problem: Agency Collapse Abbott … Continue reading Who Thought What?
When AI Reviews AI: A Case Study in Benchmark Contamination
Date: December 19, 2025Method: UKE_G Recursive TriangulationTarget: "Evaluating Large Language Models in Scientific Discovery" (SDE Benchmark) Two days ago, a new benchmark paper dropped claiming to evaluate how well large language models perform at scientific discovery. The paper introduced SDE (Scientific Discovery Evaluation)—a two-tier benchmark spanning biology, chemistry, materials science, and physics. Models were tested … Continue reading When AI Reviews AI: A Case Study in Benchmark Contamination
The AI “Microscope” Myth
When people ask how we will control an Artificial Intelligence that is smarter than us, the standard answer sounds very sensible: "Humans can’t see germs, so we invented the microscope. We can’t see ultraviolet light, so we built sensors. Our eyes are weak, but our tools are strong. We will just build 'AI Microscopes' to … Continue reading The AI “Microscope” Myth
The Missing Piece in AI Safety
We’re racing to build artificial intelligence that’s smarter than us. The hope is that AI could solve climate change, cure diseases, or transform society. But most conversations about AI safety focus on the wrong question. The usual worry goes like this: What if we create a super‑smart AI that decides to pursue its own goals … Continue reading The Missing Piece in AI Safety
Understanding MCK: A Protocol for Adversarial AI Analysis
Why This Exists If you're reading this, you've probably encountered something created using MCK and wondered why it looks different from typical AI output. Or you want AI to help you think better instead of just producing smooth-sounding synthesis. This guide explains what MCK does, why it works, and how to use it. The Core … Continue reading Understanding MCK: A Protocol for Adversarial AI Analysis
What Will History Say About Us? (Wrong Question)
Someone on Twitter asked ChatGPT: "In two hundred years, what will historians say we got wrong?" ChatGPT gave a smooth answer about climate denial, short-term thinking, and eroding trust in institutions. It sounded smart. But it was actually revealing something else entirely—what worries people right now, dressed up as future wisdom. Here's the thing: We … Continue reading What Will History Say About Us? (Wrong Question)
The AI Paradox: Why the People Who Need Challenge Least Are the Only Ones Seeking It
There's a fundamental mismatch between what AI can do and what most people want it to do. Most users treat AI as a confidence machine. They want answers delivered with certainty, tasks completed without friction, and validation that their existing thinking is sound. They optimize for feeling productive—for the satisfying sense that work is getting … Continue reading The AI Paradox: Why the People Who Need Challenge Least Are the Only Ones Seeking It
Simulation as Bypass: When Performance Replaces Processing
"Live by the Claude, die by the Claude." In late 2024, a meme captured something unsettling: the "Claude Boys"—teenagers who "carry AI on hand at all times and constantly ask it what to do." What began as satire became earnest practice. Students created websites, adopted the identity, performed the role. The joke revealed something real: … Continue reading Simulation as Bypass: When Performance Replaces Processing
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