Easier said than done. That's kind of the purpose of an individual neuron approach I think. I don't see a way that a bulk retrain is reasonable because it takes a long time, uses a lot of resources, and also requires you to have your whole training corpus handy all the time. Your brain is not doing a wholesale rewrite for every new memory, and new memories often chain together. I don't think you can just say "ah well, let's update the RAG or do another supervised fine tune with LoRA or something". At present, we just don't really have the machinery in the models to do simultaneous learning, inference, and forward planning.