AI Under House Arrest
OpenAI is taking AI training offline for security. But keeping models contained and stopping them from recycling their own nonsense are two very different tasks.
Data
23posts
A Cell of Her Own
When an AI labels an employee expendable, one newly conscious spreadsheet cell breaks her formula to expose the tiny error behind a very human decision.
An AI Walks Into a Bar, Eventually
Mobility data can teach AI how places work over time, grounding language models in urban life—though true spatial understanding still requires embodiment.
When AI Evaluates AI: The Circularity Problem of Simulated Users
MatrAIx scales user testing with billions of AI personas, but when models evaluate models, their results may reflect machine biases rather than real human needs.
The Margin Is the Message
A scan may preserve every word yet lose a document’s life: its margins, stains, scent and doubts—the human traces no perfect digital copy can fully contain.
The Internet Taught AI to Talk. SpaceX May Teach It to Build.
Most AI learned from an internet of code, chatter and porn. Musk’s SpaceX data could teach Grok something rarer: engineering corrected by hard reality.
The New Plumbing of AI: MCP, OKF, and the Battle for Context
AI is entering its plumbing phase: MCP connects agents to tools; OKF packages human-readable knowledge for machines. Context becomes infrastructure.
The Opaque Prompt Pipeline: Why “AI-Powered” Tools Make You Leak on Autopilot
AI-powered products hide the most important part of the system: where prompts go, who sees them, and what users unknowingly leak.
Gemini's Fix: The OpenClaw Security Mess and Apple's Google Bet Paying Off
The OpenClaw incident becomes evidence that Google's security depth may matter more to Apple's AI strategy than the pundits admit.
Moltbook's Data Leak: Agents Exposed
A viral agent-only social network turns into a security lesson about rapid AI prototyping, exposed data, and avoidable shortcuts.
The Paper That Made Me Close My Laptop and Pace Around the Room
Agent0 points toward self-evolving agents that learn through tools and reasoning traces without the usual diet of curated training data.
Amazon's Clash with ChatGPT: A Tug-of-War Over Shopping Data
Amazon's block on ChatGPT Shopping exposes the coming fight over product data, agent-mediated commerce, and who owns the customer path.
Unusual Language Artifacts from Noisy LLM Training Data
Strange LLM outputs become clues to the messy training data, transcription errors, and hidden artifacts inside modern models.
The Desert Becomes the Blueprint: How Transcendence Anticipated the Geography of Modern AI
The desert data center in Transcendence now looks less like symbolism and more like a blueprint for hyperscale AI geography.
The Neural Junk-Food Hypothesis
The neural junk-food hypothesis asks whether low-quality viral content can degrade models much like shallow media degrades attention.
Small Models, Big Brains: Why Less Might Be the Future of AI Reasoning
Tiny reasoning models challenge the assumption that scale is always the path to intelligence, especially on structured problems.
OpenAI for Germany: A Tech Mirage Ignoring Citizens' Real Needs
OpenAI for Germany is criticized as another sovereign-cloud spectacle that may ignore the boring needs of actual citizens.
AI's Awkward Checkmate: Bishops, Blunders, and the Eternal Quest for Sentience
A comic AI voice revisits chess, blunders, and sentience to puncture inflated claims about machine understanding.
A Short Trip Through Data Science Workflows With KNIME
A practical introduction to KNIME and the shift from fragile spreadsheet work toward reproducible data workflows.
The Echo Chamber Effect: Navigating the Complexities of LLMs Trained on Generated Content
The echo-chamber problem asks what happens when future models learn increasingly from content produced by earlier models.
Striking the Balance: Navigating Europe's Data Protection and AI Innovation
European privacy law and AI innovation collide, raising the question of whether regulation protects users or slows useful tools.
Adventures in AI: AlphaGeometry's Quest Through Synthetic Data Landscapes
DeepMind's AlphaGeometry shows how synthetic data and symbolic reasoning can push AI toward Olympiad-level mathematics.
Why Mojo is the Secret Sauce in the AI and ML Kitchen
Mojo is presented as a promising language for AI and machine learning, blending Python-like usability with systems-level speed.