It occurs to me: we have latent embedding giving 'general knowledge' to an LLM. What if we use a 'blank' LLM as well as an agent and train that blank LLM on personal context to query that as memory?
Can an LLM be trained to understand language without remembering anything else from its training data? I thought the intrinsic knowledge and the ability to understand language were tied together.
It would be closer to using an LLM as a RAG for memory, as the reasoning LLM in injected with the return of the 'memory llm' (maybe with a defined number of 'slots' for easy clean up).
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It occurs to me: we have latent embedding giving 'general knowledge' to an LLM. What if we use a 'blank' LLM as well as an agent and train that blank LLM on personal context to query that as memory?
Can an LLM be trained to understand language without remembering anything else from its training data? I thought the intrinsic knowledge and the ability to understand language were tied together.
It would be closer to using an LLM as a RAG for memory, as the reasoning LLM in injected with the return of the 'memory llm' (maybe with a defined number of 'slots' for easy clean up).