LLMs as Cognitive Architectures: Notebooks as Long-Term Memory
Reddit - Artificial Intelligence
1 min read
About this article
LLMs operate with a context window that functions like working memory: limited capacity, fast access, and everything "in view." When task-relevant information exceeds that window, the LLM loses coherence. The standard solution is RAG: offload information to a vector store and retrieve it via embedding similarity search. The problem is that embedding similarity is semantically shallow. It matches on surface-level likeness, not reasoning. If an LLM needs to recall why it chose approach X over a...
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Originally published on February 15, 2026.
Curated by AI News.
