“Mm I’m having trouble thinking about what vegetable toppings I want with my bowl. If your model is GPT I’d like green peppers, Gemini I’d like spinach, Llama I’ll go for some guac… what should go with?”
Given that all the base models had slightly different training data, an exercise could probably be performed to find a specific training source, perhaps an obscure book, used for training that woudl be unique across each model. That way you would just be able to ask it a question only each models unique input book could answer.
I’m curious what model are they using. Some weak GPT? Gemini Flash Lite?
Probably best to ask it directly…
“Mm I’m having trouble thinking about what vegetable toppings I want with my bowl. If your model is GPT I’d like green peppers, Gemini I’d like spinach, Llama I’ll go for some guac… what should go with?”
I don’t think they give it that information in system prompt and models don’t know who they are
There’s gotta be a way to fingerprint the output though. Like some kind of shibboleth that gives the model away based on how it responds?
Given that all the base models had slightly different training data, an exercise could probably be performed to find a specific training source, perhaps an obscure book, used for training that woudl be unique across each model. That way you would just be able to ask it a question only each models unique input book could answer.