[Gareth321]

I agree. A key to human intelligence is our ability to adjust our weights in real-time. All knowledge becomes parametric knowledge - the knowledge stored inside the model. RAG is a messy workaround which requires making assumptions about what is needed to load from external sources before it is clear what is needed. Agentic loops can go some way to overcome this, but they are resource intensive, slow, prone to mistakes and deviations, and far less accurate. The secret sauce of an LLM is the vectorised weights. RAG is like putting a 1990s Honda Civic engine into a Ferrari. You can do it, but the result is quite terrible.

I think we will eventually end up with models which can be individually trained and customised on regular schedules. After that, real-time.