I guess I’m wondering if there’s some way to bake the contextual understanding into the model instead of keeping it all in vram. Like if you’re talking to a person and you refer to something that happened a year ago, you might have to provide a little context and it might take them a minute, but eventually, they’ll usually remember. Same with AI, you could say, “hey remember when we talked about [x]?” and then it would recontextualize by bringing that conversation back into vram.
Seems like more or less what people do with Stable Diffusion by training custom models, or LORAs, or embeddings. It would just be interesting if it was a more automatic process as part of interacting with the AI - the model is always being updated with information about your preferences instead of having to be told explicitly.
I guess I’m wondering if there’s some way to bake the contextual understanding into the model instead of keeping it all in vram. Like if you’re talking to a person and you refer to something that happened a year ago, you might have to provide a little context and it might take them a minute, but eventually, they’ll usually remember. Same with AI, you could say, “hey remember when we talked about [x]?” and then it would recontextualize by bringing that conversation back into vram.
Seems like more or less what people do with Stable Diffusion by training custom models, or LORAs, or embeddings. It would just be interesting if it was a more automatic process as part of interacting with the AI - the model is always being updated with information about your preferences instead of having to be told explicitly.
But mostly it was just a joke.