Analysis of how licensing deals favor large publishers, leaving small publishers stranded amid AI training and content value asymmetries.
The license. Why the AI content market pays the brand-name corpus and strands the long tail.
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Digital & AI Art
124 posts
Creative industries. The bifurcated reality.
New data shows a ‘middle squeeze’ in creative jobs due to AI, with top-tier professionals augmenting and routine roles declining sharply.
The Bubble Question, Disentangled: 1999 vs 2026 Category by Category
A detailed comparison of AI investment patterns and bubble signals between 1999 dotcom era and 2026, highlighting key differences and implications.
The Ghost Story Became a Forecast.
Thorsten Meyer analyzes Jack Clark’s recent essay, revealing a bivalent forecast for AI development with significant implications for policy and research.
OpenEuroLLM. The third path.
European project OpenEuroLLM faces resource challenges amid ambitious goals for multilingual LLMs, highlighting limits of pan-European AI collaboration.
The Coding Singularity Is Real — and Steeper Than Clark Presented
New data confirms the coding singularity is accelerating faster than previously thought, with AI capabilities surpassing earlier projections and reshaping software development.
The Machine Economy — Capital-Heavy, Human-Light, Trading With Itself
Analysis of the emerging machine economy where AI-driven firms operate with minimal human labor, reshaping markets and economic structures.
The Defender’s Counter-Cascade.
On May 11, 2026, Google disclosed the first confirmed use of an AI-built zero-day exploit, signaling a shift in offensive capabilities and deployment gaps in AI-driven cybersecurity.
The Compounding Error Problem — Why 99.9% Alignment Decays to 60% in 500 Generations
Analysis of how 99.9% alignment accuracy diminishes significantly over multiple AI generations, raising concerns for recursive self-improvement safety.
The Co-Founder’s Black Hole — A Structural Read on Jack Clark’s Automated AI R&D Essay
Anthropic co-founder Jack Clark predicts over 60% chance of fully automated AI research by 2028, raising concerns about institutional capacity and future risks.
