Why AI Models Freeze After Release and What Blocks True Continuous Learning
Model weights are locked the moment an LLM is shipped, so it can only use context‑window memory, not update its long‑term knowledge. While changing weights at runtime is technically trivial, unsupervised continuous training quickly degrades performance, making reliable, self‑improving AI a major hurdle for personalization and AGI.