⊆ subset

"RAG-tagging is retrieval augmented generation plus traditional tagging. It uses LLMs to generate, shape and refine the tags allocated to saved items based on the both the user's historical context and the requirements of their interactions in the present moment, without recourse to a distant, centralised third party service and global data store.

Traditional tagging is, for the most part, a manual, one-and-done exercise. Something's tagged at point of capture and a monolothic, fragmented schema of tags emerges over time. RAG-tagging, in contrast, continually regenerates the tags applied to items in a schema that accounts for historical tagging and the needs of the present moment.

Semantic zooming (sem-zooming) complements RAG-tagging. Humans have a supposed memory span of seven things (+/- 2). Sem-zooming is the reformulation of meaning based on a combination of the resolution of the items that are viewed and a human's inherent memory span."

"RAG-tagging is retrieval augmented generation plus traditional tagging. It uses LLMs to generate, shape and refine the tags allocated to saved items based on the both the user's historical context and the requirements of their interactions in the present moment, without recourse to a distant, centralised third party service and global data store.

Traditional tagging is, for the most part, a manual, one-and-done exercise. Something's tagged at point of capture and a monolothic, fragmented schema of tags emerges over time. RAG-tagging, in contrast, continually regenerates the tags applied to items in a schema that accounts for historical tagging and the needs of the present moment.

Semantic zooming (sem-zooming) complements RAG-tagging. Humans have a supposed memory span of seven things (+/- 2). Sem-zooming is the reformulation of meaning based on a combination of the resolution of the items that are viewed and a human's inherent memory span."
https://paragraph.xyz/@subset/rag-tagging-and-sem-zooming