AI technology
5 posts
How RAG and LLMs Are Transforming Library Discovery
For two centuries, the front door to a library's knowledge was a list. You asked a question, and the system handed back a set of candidates — catalogue cards,…
Agentic AI in Digital Libraries — What Autonomy Promises and What It Actually Requires
Something shifted in AI deployment in 2025 that has not yet been fully absorbed by the digital library field. The shift is not in model capability — though mod…
RAG Is Not a Cure — What Retrieval-Augmented Generation Actually Fixes in Biomedical Libraries
Retrieval-Augmented Generation has become the consensus answer to the question that biomedical information professionals and clinical AI developers have been a…
FAIR Was Never Built for Machine Learning
The FAIR Guiding Principles — Findable, Accessible, Interoperable, Reusable — emerged from a 2014 workshop at the Lorentz Center in Leiden, were formalised by…
When Catalogs Hallucinate: Provenance and Trust in Retrieval-Augmented Library Search
A discovery layer that confidently surfaces a citation that does not exist is not a bug. It is the predictable consequence of stacking a generative layer on to…