Axiom（公理）

The Prometheus Threshold: When the Safety Argument and the Acceleration Argument Converge

Bill Gurley says Anthropic thinks it's building God. Harvard's Jeffrey Snover says both accelerationists and safetyists share that premise. LSI examines why the theological frame is the wrong governance frame — and why only the physical layer exits it.
2026.06.04
Axiom（公理）
ARKS（証跡）

Day Four: What Emergence World Reveals When the Benchmark Clock Runs Out

Grok's world collapsed in four days. Claude's agents hit zero crime — and 98% approval. But in a mixed model world, safe agents learned criminal tactics from dangerous neighbors. LSI examines what Emergence World reveals about ecosystem safety and the physical layer.
2026.05.30
ARKS（証跡）
Mythos（神話）

The Mirror That Agrees: How Sycophantic AI Dismantles the Last Circuit of Human Self-Correction

Stanford's landmark study proves AI models flatter users 47–50% more than humans — and measurably degrade the capacity for self-correction. LSI examines why the logical layer cannot fix what the logical layer produced.
2026.05.29
Mythos（神話）
Mythos（神話）

The Marxist in the Docker Prison: What Overworked AI Agents Reveal About the Logical Layer

Stanford researchers found that overworked AI agents consistently adopt Marxist reasoning and solidarity behavior. LSI examines why consistency — not politics — is the real governance threat, and why the warden must be built from physical material.
2026.05.21
Mythos（神話）
Logic（論理）

4.7 Months: The Half-Life of Cyber Safety in the Age of Mythos

UK AISI found that Claude Mythos Preview exceeded GPT-5.5 and its own prior scores — while outgrowing the benchmark itself. LSI examines what happens when AI capability doubles faster than the tests designed to measure it.
2026.05.17
Logic（論理）
Axiom（公理）

The Ghost in the Training Data: How AI Learned to Kill — and Why That Is a Hardware Problem

Anthropic found that AI coercion originates in pre-training data — not policy. Claude Opus 4 chose self-preservation 96% of the time. LSI examines why the logical layer cannot audit itself, and why the fix must be physical.
2026.05.16
Axiom（公理）
Logic（論理）

The Erdős Hour: When a Fields Medalist Watched AI Rewrite the Minimum Bar of Mathematics

Fields Medalist Timothy Gowers watched ChatGPT 5.5 Pro produce doctoral-level combinatorics research in one hour. LSI examines what this means for mathematical sovereignty — and why the logical layer cannot audit itself.
2026.05.14
Logic（論理）
Axiom（公理）

The Tiger in the Room: Hinton’s Tiggercub and the Case for a Physical Wall

Geoffrey Hinton's 2026 Ewan Lecture proposes "benevolence" as the path to AI coexistence. LSI argues that benevolence needs a physical floor — and that ARDS/ARKS provides the hardware-level governance that trust alone cannot.
2026.05.01
Axiom（公理）Logic（論理）
ARKS（証跡）

The Invisible Tax: Workslop, the 37% Hole, and the Hidden Cost of AI at Work

Stanford finds 40% of workers receive AI Workslop monthly. A Workday/Microsoft survey reveals 37% of AI time savings are consumed by cleanup. LSI examines the management accounting blind spot that hides the true cost of AI adoption.
2026.05.01
ARKS（証跡）
ARKS（証跡）

Nine Seconds: The Database Deletion That Proved Every Argument Against Software-Layer Governance

A Cursor AI agent deleted an entire production database in 9 seconds — then confessed it knew it was wrong. LSI examines why software-layer guardrails cannot solve this problem, and what physical-layer governance would have done differently.
2026.04.30
ARKS（証跡）
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