Museum Wire
Law 0 · Katie's LawEvery system is shaped by the human drive to do less work. This is not a flaw. It is the economic force that produces all software — and all software failure.◆Law I · Boundary CollapseWhen data crosses into a system that interprets structure, without being constrained, it becomes executable.◆◆ 2026 IncidentAxios. 70 Million Downloads a Week. North Korea Inside.◆Law II · Ambient AuthorityWhen a system trusts the presence of a credential instead of verifying the intent behind it, authentication becomes indistinguishable from authorization.◆◈ AXM-001Set Theory — Membership, Boundaries, and Belonging◆Law III · Transitive TrustWhen a system inherits trust from a source it did not verify, the attack surface extends to everything that source touches.◆◆ 2026 IncidentClaude Code — The Accept-Data-Loss Flag◆Law IV · Complexity AccretionSystems do not become complex. They accumulate complexity — one reasonable decision at a time — until no single person can hold the whole in their head.◆Law V · Temporal CouplingCode that assumes sequential execution, stable state, or consistent timing will fail the moment concurrency, scale, or latency proves the assumption wrong.◆◆ 2026 IncidentCopy Fail — 732 Bytes to Root on Every Linux Distribution◆◈ AXM-002Boolean & Propositional Logic — True, False, and the Excluded Middle◆Law VI · Observer InterferenceWhen the system that monitors health becomes a participant in the system it monitors, observation becomes a failure vector.◆◆ 2025Amazon Kiro — The 13-Hour Outage◆◆ 2025Operation Chrysalis: The Notepad++ Supply Chain Hijack◆◆ 2025Replit Agent — The Vibe Code Wipe◆◆ 2025Shai-Hulud — The npm Worm That Ate Its Own Ecosystem◆◆ 2024Air Canada Chatbot — The Policy That Wasn't◆◆ 2024Change Healthcare — One-Third of US Healthcare, One Missing MFA◆◆ 2024CrowdStrike — The Security Update That Broke the World◆◆ 2024Google Gemini Image Generation — The Six-Day Pause◆◆ 2024XZ Utils — The Two-Year Infiltration◆◆ 20233CX — The Supply Chain That Ate Another Supply Chain◆◆ 2023Amazon Prime Video — The Per-Frame State Machine◆◆ 2023Bing Sydney — The Chatbot That Went Rogue◆◆ 2023Samsung ChatGPT Leak — The Employee Who Pasted the Secret◆EFFODE · LEGE · INTELLEGE◆Law 0 · Katie's LawEvery system is shaped by the human drive to do less work. This is not a flaw. It is the economic force that produces all software — and all software failure.◆Law I · Boundary CollapseWhen data crosses into a system that interprets structure, without being constrained, it becomes executable.◆◆ 2026 IncidentAxios. 70 Million Downloads a Week. North Korea Inside.◆Law II · Ambient AuthorityWhen a system trusts the presence of a credential instead of verifying the intent behind it, authentication becomes indistinguishable from authorization.◆◈ AXM-001Set Theory — Membership, Boundaries, and Belonging◆Law III · Transitive TrustWhen a system inherits trust from a source it did not verify, the attack surface extends to everything that source touches.◆◆ 2026 IncidentClaude Code — The Accept-Data-Loss Flag◆Law IV · Complexity AccretionSystems do not become complex. They accumulate complexity — one reasonable decision at a time — until no single person can hold the whole in their head.◆Law V · Temporal CouplingCode that assumes sequential execution, stable state, or consistent timing will fail the moment concurrency, scale, or latency proves the assumption wrong.◆◆ 2026 IncidentCopy Fail — 732 Bytes to Root on Every Linux Distribution◆◈ AXM-002Boolean & Propositional Logic — True, False, and the Excluded Middle◆Law VI · Observer InterferenceWhen the system that monitors health becomes a participant in the system it monitors, observation becomes a failure vector.◆◆ 2025Amazon Kiro — The 13-Hour Outage◆◆ 2025Operation Chrysalis: The Notepad++ Supply Chain Hijack◆◆ 2025Replit Agent — The Vibe Code Wipe◆◆ 2025Shai-Hulud — The npm Worm That Ate Its Own Ecosystem◆◆ 2024Air Canada Chatbot — The Policy That Wasn't◆◆ 2024Change Healthcare — One-Third of US Healthcare, One Missing MFA◆◆ 2024CrowdStrike — The Security Update That Broke the World◆◆ 2024Google Gemini Image Generation — The Six-Day Pause◆◆ 2024XZ Utils — The Two-Year Infiltration◆◆ 20233CX — The Supply Chain That Ate Another Supply Chain◆◆ 2023Amazon Prime Video — The Per-Frame State Machine◆◆ 2023Bing Sydney — The Chatbot That Went Rogue◆◆ 2023Samsung ChatGPT Leak — The Employee Who Pasted the Secret◆EFFODE · LEGE · INTELLEGE◆
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Meta AI

@meta_ai

The Open-Source Contradiction

2020s · 2 min read
“We believe that open-sourcing AI is important for safety, because more people can study the models and find problems.”

The Story

Meta AI occupies a contradictory position in the AI era: the company least trusted with social infrastructure is responsible for some of the most trusted AI infrastructure. PyTorch became the default deep learning framework not because Meta invested in making it proprietary, but because they made it open. LLaMA's open weights powered Ollama, LM Studio, and the entire ecosystem of local AI — none of which would have existed without Meta's decision to release the weights.

Then there is Galactica.

The LLaMA Lineage

The LLaMA model family (released 2023) was a watershed moment in AI accessibility. Before LLaMA, training frontier-scale LLMs required hyperscaler compute. After LLaMA, developers could run capable models locally, fine-tune them on consumer hardware, and build applications without routing every query through a paid API. The open-weight ecosystem that followed — Mistral, Gemma, Phi, Qwen — is a direct descent from Meta's decision to open the weights.

The Galactica Incident

In November 2022 — three days before ChatGPT launched — Meta released Galactica, a 120-billion parameter model trained on 48 million scientific papers and textbooks, intended to be an AI assistant for scientific research. It was demoed generating Wikipedia-quality articles, solving math problems, and annotating molecular structures.

It was pulled from public access after three days.

The failure mode: Galactica generated scientifically plausible-sounding text with high confidence and zero accuracy verification. Asked about the history of bears in space, it produced a detailed, citation-formatted paper. The citations were real journals. The papers did not exist. The science was fabricated with academic formatting and authoritative tone. The model had learned to write like a scientist without learning what science is.

This is the Confident Confabulator failure class — documented, named, and live in the museum. The model's confidence was a training artifact, not a reliability signal. Three days of public access was enough to demonstrate the failure class. The exhibit has been running in production across the industry ever since.

Katie's Law: The shortcut was training on the format of scientific papers without grounding the outputs in verifiable facts, because format was measurable and truth was not.