[sqrt17]

GPT-3 is too large to be useful for practical purposes. Look it up. It's the equivalent of a Formula 1 car or a Saturn V rocket - an impressive feat of technology but of no practical relevance for getting you to work and back.

And certainly fine-tuning and distillation are part of the story why we wanted these large do-all-be-all models in the first place, but the question of what's next for the state of the art - and that currently would be featurization through a large transformer model (i.e. BERT, ERNIE, GPT-2) with some deep-but-not-huge task-specific model on top - isn't simply answered by "more compute".