You make it sound as if GPT-3 is just the same GPT-2 model with some extra Enterprise-y features thrown in. They're completely different models, trained on different data, and vastly different sizes. GPT-2 had 1.5B parameters, and GPT-3 has 175B. It's two orders of magnitude larger.
Sure, both models are using the same structures (attention layers, mostly), so it's a quantitative change rather than a qualitative change. But there's still a hell of a big difference between the two.
Sure, both models are using the same structures (attention layers, mostly), so it's a quantitative change rather than a qualitative change. But there's still a hell of a big difference between the two.