What amazes me is that all those super meta "patterns" are already embedded in GPT-3's giant model. As compared to GPT-2, where you'd need to have your own larg

What amazes me is that all those super meta "patterns" are already embedded in GPT-3's giant model. As compared to GPT-2, where you'd need to have your own large dataset to fine-tune for a specific use case/ the pattern you want to support. For instance, we fine-tuned GPT-2 against all episodes of South Park's scripts, and it took a long time to fine-tune. It kinda succeeded generating a model that "speaks south park" with pretty decent character alignment. (https://www.soulreplica.com/brodown https://www.soulreplica.com/brodown). I'm wondering if GPT-3 can achieve the same effect with just a few lines of South Park script? Does GPT-3 already know how Cartman usually talks?