While GPT-2 didn't show emergent abilities, it did show improved accuracy on various tasks with respect to GPT-1. At that point, it was clear that scaling made

While GPT-2 didn't show emergent abilities, it did show improved accuracy on various tasks with respect to GPT-1. At that point, it was clear that scaling made sense. In other words, no one expected GPT-3 to suddenly start solving tasks without training as it did, but it was expected to be useful as an incremental improvement to what GPT-2 did. At the time, GPT-2 was seeing practical use, mainly in text generation from some initial words - at that point the big scare was about massive generation of fake news - and also as a model that one could fine-tune for specific tasks. It made sense to train a larger model that would do all that better. The rest is history.