Semem : Semantic Web Memory for Intelligent Agents

Semem [1] is an experimental Node.js toolkit for AI memory management that
integrates large language models (LLMs) with Semantic Web technologies
(RDF/SPARQL). It offers knowledge graph retrieval and augmentation
algorithms within a conceptual model based on the Ragno [2] (knowledge
graph description) and ZPT [3] (knowledge graph navigation) ontologies.

The intuition is that while LLMs and associated techniques have massively
advanced the field of AI and offer considerable utility, the typical
approach is missing the elephant in the room : the Web - the biggest known
knowledgebase in our universe. Semantic Web technologies offer data
integration at a global scale, with tried & tested conceptual models for
knowledge representation. There is a lot of low-hanging fruit.

More a heads-up on what I've been playing with recently than a proper
announcement. This is an experimental project with no particular finish
line.
But I reckon it's reached a form that won't be changing fundamentally in
the near future.

[1] https://github.com/danja/semem
[2] https://github.com/danja/ragno
[3] https://github.com/danja/zpt

Cheers,
Danny.

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https://danny.ayers.name <http://hyperdata.it/danja>