It's not obvious (to me, at least), that a large language model would ever have any of the characteristics of ChatGPT. GPT-2 is neat to play around with, but it

It's not obvious (to me, at least), that a large language model would ever have any of the characteristics of ChatGPT. GPT-2 is neat to play around with, but it's just so far away from ChatGPT(-3.5 or -4) that I didn't see it coming. Nor did I see a mere denoising algorithm coming up with StableDiffusion, but here we are. Given fine-tuning of the model, and improvements allowing for a much larger context window size, I think it'll be possible for LLMs to be able to turn a class inside out and then refactor its code and translate it into another language, while generating unit tests that prove it all still works correctly. How much faster could programming language design iterate if legacy code compatibility wasn't an issue?