TechnicalAI glossary
Model collapse
The degradation of an AI trained on content produced by other AIs: from generation to generation, errors amplify and diversity fades. A growing risk as the internet fills with synthetic texts and images.
In other words
A photocopy of a photocopy: with each pass, the image loses a little more sharpness.
Alyriaz articles that mention it
- AI and journalism: what’s really at stake in the newsroom
There are fears that AI will replace journalists. The real upheaval lies elsewhere: in the collapse of the economic model that funded the news. We analyse what is actually changing in newsrooms.
- The week AI went looking for its raw material
Weekly round-up for 3–9 August 2026: data takes centre stage, prices keep tumbling, and opacity gains ground on the regulatory front. We connect the dots.
- An AI that improves itself: where exactly is the line?
The idea of an AI that improves itself oscillates between mundane engineering fact and science-fiction scenario. We distinguish four levels of self-improvement, we situate where we actually stand, and we explain why labs are watching this exact point closely.
- Nvidia teaches robots by making them dream about the consequences
Nvidia has unveiled a system that learns from videos and robot movements, then simulates the consequences of an action. We explain what this approach changes, and why it could redefine what constitutes training data.
- AI labs are buying books by the pallet, and destroying them to scan them.
AI labs are bulk-buying physical books published before 2022, touted as the last source of guaranteed human-written text. The industrial scanning destroys the volumes. We explain why this rush is happening, what it says about the state of data, and what it threatens.
- What if AI ends up poisoning itself?
Model collapse describes what happens when an AI trains on content generated by other AIs: a gradual impoverishment, like a photocopy of a photocopy. A recent study revives the concern. We explore the phenomenon and the philosophical question it raises: can an intelligence that feeds only on itself still learn?