Tag: knowledge-representation
4 items with this tag.
Higher Education Reference Model (HERM)
A shared vocabulary for universities, set out in business, data, application, and technology reference models, and a practical starting point for making institutional knowledge readable by software and AI agents.
Organising your notes for AI: why retrieval isn't enough
Most advice on organising notes for AI treats it as a retrieval problem, as if the AI only needs to find the right documents. The harder problem is translation, making the relationships in your thinking machine-readable without losing what makes them yours. This post explains why search and retrieval fall short, shows what a typed link between two notes looks like, and suggests one small way to start.
Contextual interoperability
Contextual interoperability is what lets you use your own notes, frameworks, and commitments with any AI model, local or hosted. It has two halves: the context has to be legible, with relationships a model can follow, and portable, held by you instead of inside one provider's system. With a curriculum mapping example from a pharmacy programme.
Knowledge graph
How a knowledge graph differs from a vector database: it stores entities and the typed relationships between them, so AI can reason across connections.